| | --- |
| | license: apache-2.0 |
| | base_model: facebook/wav2vec2-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: AsrTaskModel |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | [<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/hamees-iitm.ac.in/huggingface/runs/vp52o41j) |
| | # AsrTaskModel |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4220 |
| | - Wer: 0.2541 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.0001 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 1000 |
| | - num_epochs: 5 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:------:| |
| | | 3.0261 | 0.5556 | 500 | 3.1243 | 0.9989 | |
| | | 1.1139 | 1.1111 | 1000 | 0.9005 | 0.5382 | |
| | | 0.8059 | 1.6667 | 1500 | 0.6447 | 0.3916 | |
| | | 0.5712 | 2.2222 | 2000 | 0.5581 | 0.3395 | |
| | | 0.5164 | 2.7778 | 2500 | 0.4805 | 0.2998 | |
| | | 0.3958 | 3.3333 | 3000 | 0.4717 | 0.2820 | |
| | | 0.4108 | 3.8889 | 3500 | 0.4494 | 0.2692 | |
| | | 0.3403 | 4.4444 | 4000 | 0.4507 | 0.2588 | |
| | | 0.3087 | 5.0 | 4500 | 0.4220 | 0.2541 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.42.4 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
