---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: xls-r-base-300m-toratan-240
  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. -->

# xls-r-base-300m-toratan-240

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0093
- Cer: 0.0027

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.1579        | 2.0833  | 400  | 1.6854          | 0.4430 |
| 1.5758        | 4.1667  | 800  | 1.0236          | 0.2938 |
| 1.2033        | 6.25    | 1200 | 0.7921          | 0.2512 |
| 0.9625        | 8.3333  | 1600 | 0.5875          | 0.1755 |
| 0.8087        | 10.4167 | 2000 | 0.4633          | 0.1577 |
| 0.6701        | 12.5    | 2400 | 0.3454          | 0.1186 |
| 0.5412        | 14.5833 | 2800 | 0.2316          | 0.0844 |
| 0.4432        | 16.6667 | 3200 | 0.1534          | 0.0565 |
| 0.3654        | 18.75   | 3600 | 0.0914          | 0.0379 |
| 0.288         | 20.8333 | 4000 | 0.0501          | 0.0194 |
| 0.2336        | 22.9167 | 4400 | 0.0333          | 0.0117 |
| 0.2041        | 25.0    | 4800 | 0.0197          | 0.0069 |
| 0.1659        | 27.0833 | 5200 | 0.0108          | 0.0033 |
| 0.1436        | 29.1667 | 5600 | 0.0093          | 0.0027 |


### Framework versions

- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1