|
--- |
|
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: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# ./openai/whisper-medium.en-cit-do015-wd0-lr3e-06-FULL |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/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 |
|
|