|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- automatic-speech-recognition |
|
- ./sample_speech.py |
|
- generated_from_trainer |
|
model-index: |
|
- name: en-xlsr |
|
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. --> |
|
|
|
# en-xlsr |
|
|
|
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: 0.3889 |
|
- Cer: 0.1082 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- total_eval_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1500 |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Cer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 1.4503 | 1.22 | 2000 | 1.0610 | 0.2687 | |
|
| 1.0239 | 2.45 | 4000 | 0.6962 | 0.1904 | |
|
| 0.8977 | 3.67 | 6000 | 0.5945 | 0.1687 | |
|
| 0.804 | 4.9 | 8000 | 0.5328 | 0.1492 | |
|
| 0.698 | 6.12 | 10000 | 0.5014 | 0.1365 | |
|
| 0.6426 | 7.35 | 12000 | 0.4715 | 0.1322 | |
|
| 0.61 | 8.57 | 14000 | 0.4530 | 0.1258 | |
|
| 0.5709 | 9.79 | 16000 | 0.4300 | 0.1201 | |
|
| 0.5235 | 11.02 | 18000 | 0.4168 | 0.1166 | |
|
| 0.4778 | 12.24 | 20000 | 0.4057 | 0.1129 | |
|
| 0.4571 | 13.47 | 22000 | 0.3945 | 0.1100 | |
|
| 0.4388 | 14.69 | 24000 | 0.3891 | 0.1081 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
