---
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_13_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-tamil-commonvoice
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ta
      split: test
      args: ta
    metrics:
    - type: wer
      value: 1.0
      name: Wer
---

<!-- 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-large-xls-r-300m-tamil-commonvoice

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 7.9682
- Wer: 1.0

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 6.0629        | 0.7737  | 400   | 1.5761          | 0.9986 |
| 0.6711        | 1.5474  | 800   | 0.5474          | 0.7253 |
| 0.437         | 2.3211  | 1200  | 0.4898          | 0.6689 |
| 0.3691        | 3.0948  | 1600  | 0.4760          | 0.6562 |
| 0.3942        | 3.8685  | 2000  | 0.8449          | 0.7908 |
| 1.3114        | 4.6422  | 2400  | 1.8169          | 0.9883 |
| 3.0292        | 5.4159  | 2800  | 3.3102          | 1.0    |
| 3.3769        | 6.1896  | 3200  | 3.4855          | 1.0    |
| 4.0469        | 6.9632  | 3600  | 5.2510          | 1.0    |
| 6.6565        | 7.7369  | 4000  | 7.9749          | 1.0    |
| 7.9329        | 8.5106  | 4400  | 7.9682          | 1.0    |
| 7.925         | 9.2843  | 4800  | 7.9682          | 1.0    |
| 7.9128        | 10.0580 | 5200  | 7.9682          | 1.0    |
| 7.9132        | 10.8317 | 5600  | 7.9682          | 1.0    |
| 7.9118        | 11.6054 | 6000  | 7.9682          | 1.0    |
| 7.8873        | 12.3791 | 6400  | 7.9682          | 1.0    |
| 7.9357        | 13.1528 | 6800  | 7.9682          | 1.0    |
| 7.9311        | 13.9265 | 7200  | 7.9682          | 1.0    |
| 7.9049        | 14.7002 | 7600  | 7.9682          | 1.0    |
| 7.9234        | 15.4739 | 8000  | 7.9682          | 1.0    |
| 7.9521        | 16.2476 | 8400  | 7.9682          | 1.0    |
| 7.8886        | 17.0213 | 8800  | 7.9682          | 1.0    |
| 7.8915        | 17.7950 | 9200  | 7.9682          | 1.0    |
| 7.9265        | 18.5687 | 9600  | 7.9682          | 1.0    |
| 7.9366        | 19.3424 | 10000 | 7.9682          | 1.0    |
| 7.8725        | 20.1161 | 10400 | 7.9682          | 1.0    |
| 7.9321        | 20.8897 | 10800 | 7.9682          | 1.0    |
| 7.9282        | 21.6634 | 11200 | 7.9682          | 1.0    |
| 7.9025        | 22.4371 | 11600 | 7.9682          | 1.0    |
| 7.8889        | 23.2108 | 12000 | 7.9682          | 1.0    |
| 7.9366        | 23.9845 | 12400 | 7.9682          | 1.0    |
| 7.9205        | 24.7582 | 12800 | 7.9682          | 1.0    |
| 7.8946        | 25.5319 | 13200 | 7.9682          | 1.0    |
| 7.9446        | 26.3056 | 13600 | 7.9682          | 1.0    |
| 7.8891        | 27.0793 | 14000 | 7.9682          | 1.0    |
| 7.9088        | 27.8530 | 14400 | 7.9682          | 1.0    |
| 7.9546        | 28.6267 | 14800 | 7.9682          | 1.0    |
| 7.8624        | 29.4004 | 15200 | 7.9682          | 1.0    |


### Framework versions

- Transformers 4.40.1
- Pytorch 1.13.1+cu117
- Datasets 2.18.0
- Tokenizers 0.19.1