|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- automatic-speech-recognition |
|
- ./sample_speech.py |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: enko_xlsr_13p_run1 |
|
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. --> |
|
|
|
# enko_xlsr_13p_run1 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3042 |
|
- Wer: 0.1696 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- total_eval_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 0.6595 | 1.0 | 7702 | 0.4495 | 0.2974 | |
|
| 0.5717 | 2.0 | 15404 | 0.3982 | 0.2562 | |
|
| 0.5134 | 3.0 | 23106 | 0.3769 | 0.2365 | |
|
| 0.467 | 4.0 | 30808 | 0.3499 | 0.2203 | |
|
| 0.4156 | 5.0 | 38510 | 0.3391 | 0.2116 | |
|
| 0.379 | 6.0 | 46212 | 0.3327 | 0.1999 | |
|
| 0.3475 | 7.0 | 53914 | 0.3127 | 0.1947 | |
|
| 0.3105 | 8.0 | 61616 | 0.3081 | 0.1814 | |
|
| 0.281 | 9.0 | 69318 | 0.3068 | 0.1742 | |
|
| 0.2584 | 10.0 | 77020 | 0.3040 | 0.1713 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
