|
--- |
|
license: mit |
|
base_model: facebook/w2v-bert-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_17_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: only_head_const_lr_1-e4 |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: common_voice_17_0 |
|
type: common_voice_17_0 |
|
config: hy-AM |
|
split: test |
|
args: hy-AM |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.9999698904010599 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# only_head_const_lr_1-e4 |
|
|
|
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.7371 |
|
- Wer: 1.0000 |
|
- Cer: 0.8540 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
|
| 9.1084 | 1.5385 | 500 | 9.3283 | 1.5175 | 0.7359 | |
|
| 4.8706 | 3.0769 | 1000 | 5.0357 | 1.0044 | 0.8964 | |
|
| 3.8282 | 4.6154 | 1500 | 3.8866 | 0.9999 | 0.9809 | |
|
| 3.1519 | 6.1538 | 2000 | 3.1656 | 0.9998 | 0.9309 | |
|
| 2.8747 | 7.6923 | 2500 | 2.8780 | 1.0002 | 0.8692 | |
|
| 2.7465 | 9.2308 | 3000 | 2.7371 | 1.0000 | 0.8540 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
