|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-small-CV_Fleurs_AMMI_ALFFA-sw-5hrs-v1 |
|
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-small-CV_Fleurs_AMMI_ALFFA-sw-5hrs-v1 |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9973 |
|
- Wer: 0.3738 |
|
- Cer: 0.1499 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 100 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:| |
|
| 4.7293 | 1.0 | 179 | 0.2498 | 1.0815 | 0.7089 | |
|
| 1.5994 | 2.0 | 358 | 0.2279 | 0.7995 | 0.5767 | |
|
| 0.9176 | 3.0 | 537 | 0.1536 | 0.6981 | 0.4359 | |
|
| 0.4962 | 4.0 | 716 | 0.1715 | 0.6860 | 0.4339 | |
|
| 0.2817 | 5.0 | 895 | 0.1346 | 0.7140 | 0.3806 | |
|
| 0.2062 | 6.0 | 1074 | 0.1892 | 0.7249 | 0.4400 | |
|
| 0.1654 | 7.0 | 1253 | 0.1203 | 0.7535 | 0.3534 | |
|
| 0.1504 | 8.0 | 1432 | 0.1317 | 0.7843 | 0.3656 | |
|
| 0.1499 | 9.0 | 1611 | 0.1677 | 0.7990 | 0.4059 | |
|
| 0.1459 | 10.0 | 1790 | 0.1339 | 0.8195 | 0.3706 | |
|
| 0.1409 | 11.0 | 1969 | 0.1334 | 0.8332 | 0.3632 | |
|
| 0.1191 | 12.0 | 2148 | 0.1154 | 0.8286 | 0.3334 | |
|
| 0.1046 | 13.0 | 2327 | 0.1385 | 0.8617 | 0.3722 | |
|
| 0.0965 | 14.0 | 2506 | 0.1605 | 0.8756 | 0.4000 | |
|
| 0.086 | 15.0 | 2685 | 0.1258 | 0.8674 | 0.3489 | |
|
| 0.0747 | 16.0 | 2864 | 0.1688 | 0.8831 | 0.3948 | |
|
| 0.0682 | 17.0 | 3043 | 0.1257 | 0.8814 | 0.3398 | |
|
| 0.0635 | 18.0 | 3222 | 0.1366 | 0.9215 | 0.3569 | |
|
| 0.0606 | 19.0 | 3401 | 0.1271 | 0.9136 | 0.3477 | |
|
| 0.0477 | 20.0 | 3580 | 0.1273 | 0.9359 | 0.3456 | |
|
| 0.0439 | 21.0 | 3759 | 0.1286 | 0.9150 | 0.3441 | |
|
| 0.048 | 22.0 | 3938 | 0.1226 | 0.9309 | 0.3392 | |
|
| 0.0429 | 23.0 | 4117 | 0.9718 | 0.3416 | 0.1249 | |
|
| 0.0418 | 24.0 | 4296 | 0.9585 | 0.3389 | 0.1204 | |
|
| 0.042 | 25.0 | 4475 | 0.9693 | 0.3636 | 0.1361 | |
|
| 0.0353 | 26.0 | 4654 | 0.9719 | 0.3518 | 0.1309 | |
|
| 0.0329 | 27.0 | 4833 | 0.9545 | 0.3617 | 0.1424 | |
|
| 0.0288 | 28.0 | 5012 | 0.9910 | 0.3389 | 0.1257 | |
|
| 0.0298 | 29.0 | 5191 | 0.9686 | 0.3380 | 0.1264 | |
|
| 0.0242 | 30.0 | 5370 | 0.9915 | 0.3634 | 0.1488 | |
|
| 0.0225 | 31.0 | 5549 | 0.9842 | 0.3349 | 0.1279 | |
|
| 0.019 | 32.0 | 5728 | 0.9973 | 0.3738 | 0.1499 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.1 |
|
|
