| --- |
| base_model: openai/whisper-small |
| datasets: |
| - mozilla-foundation/common_voice_11_0 |
| language: |
| - mr |
| library_name: peft |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: MarathiLORA_test |
| 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. --> |
|
|
| # MarathiLORA_test |
| |
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3212 |
| |
| ## 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: 50 |
| - training_steps: 3000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 1.1553 | 0.2037 | 100 | 0.7732 | |
| | 0.6893 | 0.4073 | 200 | 0.6536 | |
| | 0.5571 | 0.6110 | 300 | 0.4662 | |
| | 0.438 | 0.8147 | 400 | 0.4299 | |
| | 0.3976 | 1.0183 | 500 | 0.4117 | |
| | 0.3582 | 1.2220 | 600 | 0.3969 | |
| | 0.3537 | 1.4257 | 700 | 0.3871 | |
| | 0.3379 | 1.6293 | 800 | 0.3749 | |
| | 0.3182 | 1.8330 | 900 | 0.3629 | |
| | 0.3198 | 2.0367 | 1000 | 0.3572 | |
| | 0.2771 | 2.2403 | 1100 | 0.3505 | |
| | 0.2886 | 2.4440 | 1200 | 0.3482 | |
| | 0.2707 | 2.6477 | 1300 | 0.3457 | |
| | 0.2777 | 2.8513 | 1400 | 0.3406 | |
| | 0.2615 | 3.0550 | 1500 | 0.3337 | |
| | 0.2361 | 3.2587 | 1600 | 0.3320 | |
| | 0.2436 | 3.4623 | 1700 | 0.3319 | |
| | 0.2375 | 3.6660 | 1800 | 0.3284 | |
| | 0.2321 | 3.8697 | 1900 | 0.3282 | |
| | 0.224 | 4.0733 | 2000 | 0.3255 | |
| | 0.211 | 4.2770 | 2100 | 0.3270 | |
| | 0.203 | 4.4807 | 2200 | 0.3257 | |
| | 0.2074 | 4.6843 | 2300 | 0.3227 | |
| | 0.2185 | 4.8880 | 2400 | 0.3234 | |
| | 0.2117 | 5.0916 | 2500 | 0.3232 | |
| | 0.1913 | 5.2953 | 2600 | 0.3228 | |
| | 0.1921 | 5.4990 | 2700 | 0.3219 | |
| | 0.1888 | 5.7026 | 2800 | 0.3217 | |
| | 0.1925 | 5.9063 | 2900 | 0.3216 | |
| | 0.1955 | 6.1100 | 3000 | 0.3212 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.12.1.dev0 |
| - Transformers 4.44.0 |
| - Pytorch 2.4.0 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
