transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:linl03/wav2vec2vncskh license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: linl03/wav2vec2vncskh
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2vncskh
  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. -->

# wav2vec2vncskh

This model is a fine-tuned version of [linl03/wav2vec2vncskh](https://huggingface.co/linl03/wav2vec2vncskh) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6088
- Wer: 0.9995

## 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: 32
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.9335        | 8.06  | 500  | 1.3712          | 1.0    |
| 1.6652        | 16.13 | 1000 | 0.7927          | 0.9995 |
| 1.2043        | 24.19 | 1500 | 0.6088          | 0.9995 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
