JackismyShephard
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Browse filesFill out empty sections in auto-generated README
Update README.md
update readme
- .gitattributes +35 -0
- README.md +91 -0
- added_tokens.json +4 -0
- config.json +92 -0
- generation_config.json +9 -0
- model.safetensors +3 -0
- preprocessor_config.json +19 -0
- runs/Jan14_01-59-01_Christians-Desktop/events.out.tfevents.1705193943.Christians-Desktop.157984.0 +3 -0
- runs/Jan14_01-59-01_Christians-Desktop/events.out.tfevents.1705281827.Christians-Desktop.157984.1 +3 -0
- runs/Jan15_09-07-38_Christians-Desktop/events.out.tfevents.1705306078.Christians-Desktop.157984.2 +3 -0
- runs/Jan15_09-07-38_Christians-Desktop/events.out.tfevents.1705367613.Christians-Desktop.157984.3 +3 -0
- special_tokens_map.json +13 -0
- spm_char.model +3 -0
- tokenizer_config.json +63 -0
- training_args.bin +3 -0
.gitattributes
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README.md
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---
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language:
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- da
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license: mit
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base_model: microsoft/speecht5_tts
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tags:
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- generated_from_trainer
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datasets:
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- alexandrainst/nst-da
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model-index:
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- name: speecht5_tts-finetuned-nst-da
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results: []
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metrics:
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- mse
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pipeline_tag: text-to-speech
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---
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# speecht5_tts-finetuned-nst-da
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the NST Danish ASR Database dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3738
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## Model description
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Given that danish is a low-resource language, not many open-source implementations of a danish text-to-speech synthesizer are available online. As of writing, the only other existing implementations available on 🤗 are [facebook/seamless-streaming](https://huggingface.co/facebook/seamless-streaming) and [audo/seamless-m4t-v2-large](https://huggingface.co/audo/seamless-m4t-v2-large). This model has been developed to provide a simpler alternative that still performs reasonable well, both in terms of output quality and inference time. Additionally, contrary to the aforementioned models, this model also has an associated Space on 🤗 at [JackismyShephard/danish-speech-synthesis](https://huggingface.co/spaces/JackismyShephard/danish-speech-synthesis) which provides an easy interface for danish text-to-speech synthesis, as well as optional speech enhancement.
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## Intended uses & limitations
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The model is intended for danish text-to-speech synthesis.
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The model does not recognize special symbols such as "æ", "ø" and "å", as it uses the default tokenizer of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts). The model performs best for short to medium length input text and expects input text to contain no more than 600 vocabulary tokens. Additionally, for best performance the model should be given a danish speaker embedding, ideally generated from an audio clip from the training split of [alexandrainst/nst-da](https://huggingface.co/datasets/alexandrainst/nst-da) using [speechbrain/spkrec-xvect-voxceleb](https://huggingface.co/speechbrain/spkrec-xvect-voxceleb).
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The output of the model is a log-mel spectogram, which should be converted to a waveform using [microsoft/speecht5_hifigan](https://huggingface.co/microsoft/speecht5_hifigan). For better quality output the resulting waveform can be enhanced using [ResembleAI/resemble-enhance](https://huggingface.co/ResembleAI/resemble-enhance).
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An example script showing how to use the model for inference can be found [here](https://github.com/JackismyShephard/hugging-face-audio-course/blob/main/finetuned_nst-da-inference.ipynb).
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## Training and evaluation data
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The model was trained and evaluated on [alexandrainst/nst-da](https://huggingface.co/datasets/alexandrainst/nst-da) using MSE as both loss and metric.
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## Training procedure
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The script used for training the model can be found [here](https://github.com/JackismyShephard/hugging-face-audio-course/blob/main/finetuned-nst-da-training.ipynb)
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 20
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 0.463 | 1.0 | 4715 | 0.4169 |
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| 0.4302 | 2.0 | 9430 | 0.3963 |
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| 0.447 | 3.0 | 14145 | 0.3883 |
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| 0.4283 | 4.0 | 18860 | 0.3847 |
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| 0.394 | 5.0 | 23575 | 0.3830 |
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| 0.3934 | 6.0 | 28290 | 0.3812 |
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| 0.3928 | 7.0 | 33005 | 0.3795 |
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| 0.4123 | 8.0 | 37720 | 0.3781 |
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| 0.3851 | 9.0 | 42435 | 0.3785 |
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| 0.4234 | 10.0 | 47150 | 0.3783 |
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| 0.3781 | 11.0 | 51865 | 0.3759 |
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| 0.3951 | 12.0 | 56580 | 0.3782 |
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| 0.4073 | 13.0 | 61295 | 0.3757 |
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| 0.4278 | 14.0 | 66010 | 0.3768 |
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| 0.4172 | 15.0 | 70725 | 0.3747 |
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| 0.3854 | 16.0 | 75440 | 0.3753 |
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| 0.4876 | 17.0 | 80155 | 0.3741 |
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| 0.432 | 18.0 | 84870 | 0.3738 |
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| 0.4435 | 19.0 | 89585 | 0.3745 |
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| 0.4255 | 20.0 | 94300 | 0.3739 |
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### Framework versions
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- Transformers 4.37.0.dev0
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- Pytorch 2.1.2+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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added_tokens.json
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{
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"<ctc_blank>": 80,
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"<mask>": 79
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}
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config.json
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{
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"_name_or_path": "microsoft/speecht5_tts",
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"activation_dropout": 0.1,
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"apply_spec_augment": true,
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"architectures": [
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"SpeechT5ForTextToSpeech"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 0,
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"conv_bias": false,
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"conv_dim": [
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512,
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512,
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512,
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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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],
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"conv_stride": [
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5,
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],
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"decoder_attention_heads": 12,
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"decoder_ffn_dim": 3072,
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"decoder_layerdrop": 0.1,
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"decoder_layers": 6,
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"decoder_start_token_id": 2,
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"encoder_attention_heads": 12,
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"encoder_ffn_dim": 3072,
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"encoder_layerdrop": 0.1,
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"encoder_layers": 12,
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"encoder_max_relative_position": 160,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_norm": "group",
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"feat_proj_dropout": 0.0,
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"guided_attention_loss_num_heads": 2,
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"guided_attention_loss_scale": 10.0,
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"guided_attention_loss_sigma": 0.4,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"is_encoder_decoder": true,
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"layer_norm_eps": 1e-05,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.05,
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"max_length": 1876,
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"max_speech_positions": 1876,
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"max_text_positions": 600,
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"model_type": "speecht5",
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"num_conv_pos_embedding_groups": 16,
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"num_conv_pos_embeddings": 128,
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"num_feat_extract_layers": 7,
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"num_mel_bins": 80,
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"pad_token_id": 1,
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"positional_dropout": 0.1,
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"reduction_factor": 2,
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"scale_embedding": false,
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"speaker_embedding_dim": 512,
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"speech_decoder_postnet_dropout": 0.5,
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"speech_decoder_postnet_kernel": 5,
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"speech_decoder_postnet_layers": 5,
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"speech_decoder_postnet_units": 256,
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"speech_decoder_prenet_dropout": 0.5,
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"speech_decoder_prenet_layers": 2,
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"speech_decoder_prenet_units": 256,
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"torch_dtype": "float32",
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"transformers_version": "4.37.0.dev0",
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"use_cache": false,
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"use_guided_attention_loss": true,
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"vocab_size": 81
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"eos_token_id": 2,
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"max_length": 1876,
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"pad_token_id": 1,
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"transformers_version": "4.37.0.dev0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6fd7115b5fd692e5b4e818cec73302c5178be23b813a6666edfc2e62bb6b3365
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size 577789320
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preprocessor_config.json
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{
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"do_normalize": false,
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"feature_extractor_type": "SpeechT5FeatureExtractor",
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"feature_size": 1,
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"fmax": 7600,
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"fmin": 80,
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"padding_side": "right",
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"padding_value": 0.0,
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"processor_class": "SpeechT5Processor",
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"reduction_factor": 2,
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"return_attention_mask": true,
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"sampling_rate": 16000,
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"win_function": "hann_window",
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"win_length": 64
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}
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runs/Jan14_01-59-01_Christians-Desktop/events.out.tfevents.1705193943.Christians-Desktop.157984.0
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version https://git-lfs.github.com/spec/v1
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size 2263807
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runs/Jan14_01-59-01_Christians-Desktop/events.out.tfevents.1705281827.Christians-Desktop.157984.1
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:c977686d449c8a0bc10d6de559a807799b3f699db62037bafacaab0c36a85700
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size 364
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runs/Jan15_09-07-38_Christians-Desktop/events.out.tfevents.1705306078.Christians-Desktop.157984.2
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version https://git-lfs.github.com/spec/v1
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oid sha256:9f3d84c4307cb86f619288832906f710c7610f61781d26c0fc8c26ec132c12db
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size 762165
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runs/Jan15_09-07-38_Christians-Desktop/events.out.tfevents.1705367613.Christians-Desktop.157984.3
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version https://git-lfs.github.com/spec/v1
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oid sha256:5e8960e4c085032fb63151881c6a320a53e81bfd578b6deabdab9b29c1556981
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special_tokens_map.json
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{
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"bos_token": "<s>",
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},
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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spm_char.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:7fcc48f3e225f627b1641db410ceb0c8649bd2b0c982e150b03f8be3728ab560
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size 238473
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tokenizer_config.json
ADDED
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{
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"single_word": false,
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"special": true
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"1": {
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"single_word": false,
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"special": true
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"2": {
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"single_word": false,
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"special": true
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},
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"3": {
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"lstrip": false,
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"single_word": false,
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"special": true
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},
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"79": {
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"content": "<mask>",
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"lstrip": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"80": {
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": false
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}
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},
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "</s>",
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"model_max_length": 600,
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"pad_token": "<pad>",
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"processor_class": "SpeechT5Processor",
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"sp_model_kwargs": {},
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"tokenizer_class": "SpeechT5Tokenizer",
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"unk_token": "<unk>"
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2ab472663086f916e33cf2c755647d5168c72207604e204f721d54f6d82a7734
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size 4920
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