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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: 6e-5_4000eval |
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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: 0.2470857142857143 |
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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/%3Cmy-amazing-projecttokenizer6e-5eval4000%3E/runs/c41b6hhn) |
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# 6e-5_4000eval |
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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: 0.8508 |
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- Wer: 0.2471 |
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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: 6e-05 |
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- train_batch_size: 32 |
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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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- 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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| No log | 7.5758 | 250 | 5.4590 | 0.9995 | |
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| 9.3761 | 15.1515 | 500 | 3.7020 | 0.9995 | |
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| 9.3761 | 22.7273 | 750 | 3.0706 | 0.9995 | |
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| 3.2176 | 30.3030 | 1000 | 3.0517 | 0.9995 | |
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| 3.2176 | 37.8788 | 1250 | 1.8920 | 0.7721 | |
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| 2.0444 | 45.4545 | 1500 | 1.3641 | 0.3488 | |
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| 2.0444 | 53.0303 | 1750 | 1.1031 | 0.2779 | |
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| 0.8363 | 60.6061 | 2000 | 1.1269 | 0.2679 | |
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| 0.8363 | 68.1818 | 2250 | 1.0291 | 0.2656 | |
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| 0.6824 | 75.7576 | 2500 | 0.9712 | 0.2629 | |
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| 0.6824 | 83.3333 | 2750 | 0.8902 | 0.2619 | |
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| 0.5956 | 90.9091 | 3000 | 0.8432 | 0.2441 | |
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| 0.5956 | 98.4848 | 3250 | 0.8714 | 0.2485 | |
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| 0.4071 | 106.0606 | 3500 | 0.8222 | 0.2478 | |
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| 0.4071 | 113.6364 | 3750 | 0.8398 | 0.2501 | |
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| 0.4479 | 121.2121 | 4000 | 0.8508 | 0.2471 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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