|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-xlsr-53-ft-ccv-en-cy |
|
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. --> |
|
|
|
# wav2vec2-xlsr-53-ft-ccv-en-cy |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2765 |
|
- Wer: 0.2115 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 800 |
|
- training_steps: 9000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 5.9898 | 0.25 | 500 | 1.3093 | 0.7971 | |
|
| 1.0749 | 0.5 | 1000 | 0.5816 | 0.4617 | |
|
| 0.4332 | 0.75 | 1500 | 0.4834 | 0.4091 | |
|
| 0.3303 | 1.01 | 2000 | 0.4203 | 0.3419 | |
|
| 0.276 | 1.26 | 2500 | 0.3910 | 0.3186 | |
|
| 0.2591 | 1.51 | 3000 | 0.3901 | 0.3067 | |
|
| 0.2501 | 1.76 | 3500 | 0.3646 | 0.2895 | |
|
| 0.224 | 2.01 | 4000 | 0.3517 | 0.2806 | |
|
| 0.182 | 2.26 | 4500 | 0.3348 | 0.2656 | |
|
| 0.1777 | 2.51 | 5000 | 0.3277 | 0.2612 | |
|
| 0.1734 | 2.77 | 5500 | 0.3323 | 0.2643 | |
|
| 0.1629 | 3.02 | 6000 | 0.3171 | 0.2485 | |
|
| 0.1338 | 3.27 | 6500 | 0.3103 | 0.2398 | |
|
| 0.1292 | 3.52 | 7000 | 0.2934 | 0.2268 | |
|
| 0.1264 | 3.77 | 7500 | 0.2923 | 0.2248 | |
|
| 0.118 | 4.02 | 8000 | 0.2880 | 0.2193 | |
|
| 0.0996 | 4.27 | 8500 | 0.2793 | 0.2124 | |
|
| 0.0969 | 4.52 | 9000 | 0.2765 | 0.2115 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
