| --- |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper_tiny_char |
| 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. --> |
|
|
| # whisper_tiny_char |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3979 |
| - Wer: 100.0 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: constant |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-----:| |
| | 1.1664 | 1.0 | 859 | 0.5140 | 100.0 | |
| | 0.5122 | 2.0 | 1718 | 0.4044 | 100.0 | |
| | 0.4035 | 3.0 | 2577 | 0.3596 | 100.0 | |
| | 0.3403 | 4.0 | 3436 | 0.3394 | 100.0 | |
| | 0.2967 | 5.0 | 4295 | 0.3395 | 100.0 | |
| | 0.2582 | 6.0 | 5154 | 0.3314 | 100.0 | |
| | 0.2286 | 7.0 | 6013 | 0.3571 | 100.0 | |
| | 0.2034 | 8.0 | 6872 | 0.3590 | 100.0 | |
| | 0.181 | 9.0 | 7731 | 0.3706 | 100.0 | |
| | 0.1618 | 10.0 | 8590 | 0.3979 | 100.0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.44.0 |
| - Pytorch 2.3.1 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
