|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-large |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- sage-bergerson/edacc_processed |
|
model-index: |
|
- name: Whisper Large EdAcc |
|
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 Large EdAcc |
|
|
|
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the EdAcc dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.0862 |
|
|
|
## 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-06 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 0.8893 | 0.6494 | 200 | 0.6173 | |
|
| 0.4959 | 1.2987 | 400 | 0.5871 | |
|
| 0.4654 | 1.9481 | 600 | 0.5799 | |
|
| 0.308 | 2.5974 | 800 | 0.6095 | |
|
| 0.2504 | 3.2468 | 1000 | 0.6823 | |
|
| 0.1877 | 3.8961 | 1200 | 0.6828 | |
|
| 0.1028 | 4.5455 | 1400 | 0.7804 | |
|
| 0.0896 | 5.1948 | 1600 | 0.8240 | |
|
| 0.0516 | 5.8442 | 1800 | 0.8491 | |
|
| 0.0291 | 6.4935 | 2000 | 0.9035 | |
|
| 0.0276 | 7.1429 | 2200 | 0.9402 | |
|
| 0.0141 | 7.7922 | 2400 | 0.9443 | |
|
| 0.0098 | 8.4416 | 2600 | 0.9972 | |
|
| 0.0073 | 9.0909 | 2800 | 1.0118 | |
|
| 0.0056 | 9.7403 | 3000 | 1.0176 | |
|
| 0.0027 | 10.3896 | 3200 | 1.0468 | |
|
| 0.0021 | 11.0390 | 3400 | 1.0564 | |
|
| 0.0016 | 11.6883 | 3600 | 1.0703 | |
|
| 0.0009 | 12.3377 | 3800 | 1.0840 | |
|
| 0.0011 | 12.9870 | 4000 | 1.0862 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.3.1 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
