|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-medium |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- QEC |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-medium-quartr |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Quartr Earnings Calls |
|
type: QEC |
|
args: 'config: en, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 22.31368880573745 |
|
--- |
|
|
|
<!-- 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-medium-quartr |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Quartr Earnings Calls dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6825 |
|
- Wer: 22.3137 |
|
|
|
## 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: 8.120528078446462e-06 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine_with_restarts |
|
- lr_scheduler_warmup_steps: 84 |
|
- training_steps: 1500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.5817 | 0.32 | 100 | 0.5708 | 21.9832 | |
|
| 0.5817 | 0.64 | 200 | 0.5332 | 20.1559 | |
|
| 0.5253 | 0.96 | 300 | 0.5127 | 25.4256 | |
|
| 0.3177 | 1.28 | 400 | 0.5276 | 28.5688 | |
|
| 0.3603 | 1.61 | 500 | 0.5195 | 22.2950 | |
|
| 0.3374 | 1.93 | 600 | 0.5101 | 24.3343 | |
|
| 0.1734 | 2.25 | 700 | 0.5530 | 23.1743 | |
|
| 0.2002 | 2.57 | 800 | 0.5525 | 21.1537 | |
|
| 0.1894 | 2.89 | 900 | 0.5589 | 21.7774 | |
|
| 0.0868 | 3.21 | 1000 | 0.6291 | 23.4487 | |
|
| 0.0931 | 3.53 | 1100 | 0.6410 | 21.9208 | |
|
| 0.1094 | 3.85 | 1200 | 0.6339 | 22.5008 | |
|
| 0.1007 | 4.17 | 1300 | 0.6698 | 21.7524 | |
|
| 0.0652 | 4.49 | 1400 | 0.6820 | 22.3262 | |
|
| 0.0614 | 4.82 | 1500 | 0.6825 | 22.3137 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.1.dev0 |
|
- Tokenizers 0.15.2 |
|
|
