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---
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
|