|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-large-xlsr-en-demo |
|
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-large-xlsr-en-demo |
|
|
|
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1356 |
|
- Wer: 0.2015 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 5.3911 | 0.5 | 500 | 0.5397 | 0.2615 | |
|
| 0.3413 | 1.01 | 1000 | 0.1423 | 0.2137 | |
|
| 0.243 | 1.51 | 1500 | 0.1458 | 0.2210 | |
|
| 0.2232 | 2.01 | 2000 | 0.1380 | 0.2143 | |
|
| 0.162 | 2.51 | 2500 | 0.1464 | 0.2149 | |
|
| 0.1384 | 3.02 | 3000 | 0.1348 | 0.2109 | |
|
| 0.1164 | 3.52 | 3500 | 0.1324 | 0.2040 | |
|
| 0.1103 | 4.02 | 4000 | 0.1310 | 0.2051 | |
|
| 0.0857 | 4.53 | 4500 | 0.1356 | 0.2015 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.12.1 |
|
|
