metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./openai/whisper-medium.en-cit-do015-wd0-lr3e-06-FULL
results: []
./openai/whisper-medium.en-cit-do015-wd0-lr3e-06-FULL
This model is a fine-tuned version of openai/whisper-medium.en on the FULL dataset. It achieves the following results on the evaluation set:
- Loss: 0.6528
- Wer Ortho: 32.2429
- Wer: 22.4370
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: 3e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.8096 | 0.4773 | 50 | 1.2178 | 42.1611 | 31.5966 |
| 1.1953 | 0.9547 | 100 | 0.9199 | 37.1498 | 27.2773 |
| 0.9212 | 1.4320 | 150 | 0.8408 | 34.7486 | 25.2605 |
| 0.8448 | 1.9093 | 200 | 0.7837 | 33.6001 | 24.5210 |
| 0.7174 | 2.3866 | 250 | 0.7344 | 32.5039 | 22.9076 |
| 0.6519 | 2.8640 | 300 | 0.7002 | 33.3391 | 23.4958 |
| 0.5866 | 3.3413 | 350 | 0.6802 | 32.2429 | 22.7395 |
| 0.5625 | 3.8186 | 400 | 0.6631 | 32.6083 | 22.8067 |
| 0.5207 | 4.2959 | 450 | 0.6548 | 32.6779 | 22.8908 |
| 0.5059 | 4.7733 | 500 | 0.6528 | 32.2429 | 22.4370 |
Framework versions
- Transformers 4.42.4
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1