---
language:
- ta
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_6_1
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-ta
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MOZILLA-FOUNDATION/COMMON_VOICE_6_1 - TA
      type: common_voice_6_1
      config: ta
      split: test
      args: 'Config: ta, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.7095686384712659
---

<!-- 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-common_voice-ta

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_6_1 - TA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6563
- Wer: 0.7096

## 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: 0.0003
- 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.84  | 100  | 4.3941          | 1.0    |
| No log        | 1.69  | 200  | 3.2005          | 1.0    |
| No log        | 2.53  | 300  | 2.7844          | 1.0145 |
| No log        | 3.38  | 400  | 0.8691          | 1.0003 |
| 4.317         | 4.22  | 500  | 0.6846          | 0.8394 |
| 4.317         | 5.06  | 600  | 0.6270          | 0.7790 |
| 4.317         | 5.91  | 700  | 0.5935          | 0.7802 |
| 4.317         | 6.75  | 800  | 0.5701          | 0.7812 |
| 4.317         | 7.59  | 900  | 0.5649          | 0.7891 |
| 0.3656        | 8.44  | 1000 | 0.6092          | 0.8178 |
| 0.3656        | 9.28  | 1100 | 0.6093          | 0.7721 |
| 0.3656        | 10.13 | 1200 | 0.6154          | 0.7287 |
| 0.3656        | 10.97 | 1300 | 0.6284          | 0.7408 |
| 0.3656        | 11.81 | 1400 | 0.6343          | 0.7143 |
| 0.1681        | 12.66 | 1500 | 0.6523          | 0.7363 |
| 0.1681        | 13.5  | 1600 | 0.6543          | 0.7139 |
| 0.1681        | 14.35 | 1700 | 0.6599          | 0.7094 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1