|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-base-CALLCENTER |
|
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-base-CALLCENTER |
|
|
|
This model is a fine-tuned version of [Niccogrillo/wav2vec2-base-CALLCENTER](https://huggingface.co/Niccogrillo/wav2vec2-base-CALLCENTER) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4605 |
|
- Wer: 0.2139 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 6.9258 | 0.41 | 500 | 2.6959 | 0.9996 | |
|
| 0.7059 | 0.82 | 1000 | 0.6081 | 0.2841 | |
|
| 0.1633 | 1.22 | 1500 | 0.5037 | 0.2302 | |
|
| 0.2361 | 1.63 | 2000 | 0.4207 | 0.2206 | |
|
| 0.2289 | 2.04 | 2500 | 0.4433 | 0.2184 | |
|
| 0.1794 | 2.45 | 3000 | 0.4648 | 0.2172 | |
|
| 0.1827 | 2.86 | 3500 | 0.4592 | 0.2151 | |
|
| 0.1844 | 3.27 | 4000 | 0.4507 | 0.2143 | |
|
| 0.1723 | 3.67 | 4500 | 0.4561 | 0.2143 | |
|
| 0.1762 | 4.08 | 5000 | 0.4633 | 0.2143 | |
|
| 0.1762 | 4.49 | 5500 | 0.4610 | 0.2140 | |
|
| 0.1552 | 4.9 | 6000 | 0.4605 | 0.2139 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.13.3 |
|
|
