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output2

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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End of training

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Files changed (11) hide show
  1. README.md +121 -0
  2. config.json +118 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +9 -0
  5. runs/Nov26_07-10-08_8448cbfff26e/events.out.tfevents.1700982910.8448cbfff26e.1860.0 +3 -0
  6. runs/Nov26_07-17-46_8448cbfff26e/events.out.tfevents.1700983372.8448cbfff26e.1860.1 +3 -0
  7. runs/Nov26_07-24-37_8448cbfff26e/events.out.tfevents.1700983785.8448cbfff26e.1860.2 +3 -0
  8. runs/Nov26_07-37-56_8448cbfff26e/events.out.tfevents.1700984581.8448cbfff26e.1860.3 +3 -0
  9. runs/Nov26_07-44-12_8448cbfff26e/events.out.tfevents.1700984958.8448cbfff26e.1860.4 +3 -0
  10. runs/Nov26_07-51-41_8448cbfff26e/events.out.tfevents.1700985402.8448cbfff26e.1860.5 +3 -0
  11. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: output2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # output2
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7711
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+ - Wer: 0.3693
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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_steps: 1000
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 0.9858 | 0.5 | 500 | 0.8322 | 0.6842 |
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+ | 0.7867 | 1.0 | 1000 | 0.6777 | 0.6137 |
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+ | 0.6252 | 1.5 | 1500 | 0.6082 | 0.5503 |
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+ | 0.5833 | 2.0 | 2000 | 0.5441 | 0.5066 |
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+ | 0.4611 | 2.5 | 2500 | 0.5498 | 0.4922 |
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+ | 0.4511 | 3.0 | 3000 | 0.5262 | 0.4654 |
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+ | 0.37 | 3.5 | 3500 | 0.5422 | 0.4554 |
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+ | 0.375 | 4.0 | 4000 | 0.6414 | 0.4659 |
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+ | 0.3149 | 4.5 | 4500 | 0.5149 | 0.4353 |
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+ | 0.3103 | 5.0 | 5000 | 0.5329 | 0.4423 |
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+ | 0.2735 | 5.5 | 5500 | 0.9014 | 0.4359 |
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+ | 0.2711 | 6.0 | 6000 | 3.1838 | 0.4374 |
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+ | 0.26 | 6.5 | 6500 | 0.5987 | 0.4288 |
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+ | 0.2451 | 7.0 | 7000 | 0.5245 | 0.4206 |
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+ | 0.2184 | 7.5 | 7500 | 0.5627 | 0.4138 |
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+ | 0.2115 | 8.0 | 8000 | 0.6408 | 0.4245 |
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+ | 0.187 | 8.5 | 8500 | 0.5788 | 0.4093 |
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+ | 0.1955 | 9.0 | 9000 | 0.5591 | 0.4214 |
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+ | 0.1725 | 9.5 | 9500 | 0.5812 | 0.4135 |
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+ | 0.1758 | 10.0 | 10000 | 0.5863 | 0.4051 |
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+ | 0.1592 | 10.5 | 10500 | 0.6263 | 0.4116 |
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+ | 0.1576 | 11.0 | 11000 | 0.5829 | 0.4028 |
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+ | 0.1427 | 11.5 | 11500 | 0.6378 | 0.4016 |
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+ | 0.1476 | 12.0 | 12000 | 0.5706 | 0.3988 |
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+ | 0.1289 | 12.5 | 12500 | 0.6381 | 0.4104 |
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+ | 0.1366 | 13.0 | 13000 | 0.6326 | 0.3975 |
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+ | 0.1183 | 13.5 | 13500 | 0.6256 | 0.3916 |
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+ | 0.1225 | 14.0 | 14000 | 0.6376 | 0.3971 |
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+ | 0.1083 | 14.5 | 14500 | 0.6493 | 0.3905 |
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+ | 0.1134 | 15.0 | 15000 | 0.6686 | 0.3951 |
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+ | 0.1003 | 15.5 | 15500 | 0.6983 | 0.3967 |
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+ | 0.104 | 16.0 | 16000 | 0.6324 | 0.3927 |
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+ | 0.0928 | 16.5 | 16500 | 0.6482 | 0.3907 |
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+ | 0.0944 | 17.0 | 17000 | 0.6790 | 0.3912 |
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+ | 0.0925 | 17.5 | 17500 | 0.6877 | 0.3902 |
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+ | 0.0847 | 18.0 | 18000 | 0.6572 | 0.3845 |
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+ | 0.0808 | 18.5 | 18500 | 0.6551 | 0.3910 |
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+ | 0.0836 | 19.0 | 19000 | 0.6832 | 0.3859 |
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+ | 0.0757 | 19.5 | 19500 | 0.7594 | 0.3905 |
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+ | 0.0751 | 20.0 | 20000 | 0.6960 | 0.3880 |
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+ | 0.0715 | 20.5 | 20500 | 0.7244 | 0.3840 |
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+ | 0.07 | 21.0 | 21000 | 0.7233 | 0.3848 |
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+ | 0.0654 | 21.5 | 21500 | 0.7428 | 0.3833 |
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+ | 0.0657 | 22.0 | 22000 | 0.7014 | 0.3842 |
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+ | 0.0641 | 22.5 | 22500 | 0.7357 | 0.3796 |
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+ | 0.0624 | 23.0 | 23000 | 0.7338 | 0.3796 |
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+ | 0.0575 | 23.5 | 23500 | 0.7375 | 0.3804 |
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+ | 0.0578 | 24.0 | 24000 | 0.7386 | 0.3782 |
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+ | 0.0542 | 24.5 | 24500 | 0.7405 | 0.3758 |
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+ | 0.0509 | 25.0 | 25000 | 0.7719 | 0.3774 |
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+ | 0.0495 | 25.5 | 25500 | 0.7505 | 0.3763 |
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+ | 0.0521 | 26.0 | 26000 | 0.7345 | 0.3742 |
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+ | 0.0477 | 26.5 | 26500 | 0.7776 | 0.3740 |
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+ | 0.0442 | 27.0 | 27000 | 0.7742 | 0.3738 |
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+ | 0.0473 | 27.5 | 27500 | 0.7695 | 0.3719 |
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+ | 0.0452 | 28.0 | 28000 | 0.7737 | 0.3705 |
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+ | 0.0425 | 28.5 | 28500 | 0.7937 | 0.3702 |
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+ | 0.0415 | 29.0 | 29000 | 0.7970 | 0.3713 |
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+ | 0.0432 | 29.5 | 29500 | 0.7714 | 0.3700 |
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+ | 0.041 | 30.0 | 30000 | 0.7711 | 0.3693 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/wav2vec2-base",
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+ "activation_dropout": 0.0,
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+ "adapter_attn_dim": null,
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+ "architectures": [
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+ "Wav2Vec2ForCTC"
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+ "attention_dropout": 0.1,
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+ "codevector_dim": 256,
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+ "feat_extract_activation": "gelu",
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+ "feat_quantizer_dropout": 0.0,
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+ "freeze_feat_extract_train": true,
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+ "layer_norm_eps": 1e-05,
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+ "layerdrop": 0.0,
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+ "mask_channel_length": 10,
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+ "mask_channel_other": 0.0,
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+ "mask_channel_prob": 0.0,
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+ "mask_channel_selection": "static",
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+ "mask_feature_min_masks": 0,
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+ "mask_feature_prob": 0.0,
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+ "model_type": "wav2vec2",
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+ "no_mask_channel_overlap": false,
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+ "num_adapter_layers": 3,
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+ "num_attention_heads": 12,
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+ "num_codevector_groups": 2,
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+ "num_codevectors_per_group": 320,
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+ "num_conv_pos_embedding_groups": 16,
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+ "num_conv_pos_embeddings": 128,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "use_weighted_layer_sum": false,
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+ "vocab_size": 32,
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+ "xvector_output_dim": 512
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+ }
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