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---
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license: apache-2.0
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base_model: facebook/wav2vec2-base-960h
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tags:
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- generated_from_trainer
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datasets:
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- ami
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metrics:
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- wer
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model-index:
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- name: my_awesome_asr_mind_model
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: ami
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type: ami
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config: ihm
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split: None
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args: ihm
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metrics:
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- name: Wer
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type: wer
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value: 0.2439744220363994
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jadorantes2-utep/huggingface/runs/3reuf32f)
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# my_awesome_asr_mind_model
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the ami dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9699
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- Wer: 0.2440
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: 500
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- training_steps: 4000
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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 | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.9924 | 20.0 | 1000 | 2.4484 | 0.2986 |
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| 0.6182 | 40.0 | 2000 | 1.1429 | 0.2735 |
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| 0.4255 | 60.0 | 3000 | 0.9063 | 0.2459 |
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| 0.396 | 80.0 | 4000 | 0.9699 | 0.2440 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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