---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
model-index:
- name: ja-xlsr
  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. -->

# ja-xlsr

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5952
- Cer: 0.3240

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 300

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.9138        | 6.52   | 150  | 4.7965          | 1.0    |
| 4.7484        | 13.04  | 300  | 4.6081          | 1.0    |
| 4.5894        | 19.57  | 450  | 4.4697          | 0.9851 |
| 4.2024        | 26.09  | 600  | 4.0373          | 0.9077 |
| 2.7314        | 32.61  | 750  | 2.5507          | 0.5341 |
| 1.2293        | 39.13  | 900  | 2.0146          | 0.4139 |
| 0.5544        | 45.65  | 1050 | 1.9821          | 0.3556 |
| 0.3224        | 52.17  | 1200 | 2.0190          | 0.3587 |
| 0.1951        | 58.7   | 1350 | 2.1229          | 0.3612 |
| 0.1539        | 65.22  | 1500 | 2.1114          | 0.3470 |
| 0.1165        | 71.74  | 1650 | 2.2748          | 0.3315 |
| 0.1119        | 78.26  | 1800 | 2.2391          | 0.3488 |
| 0.0989        | 84.78  | 1950 | 2.3438          | 0.3383 |
| 0.0915        | 91.3   | 2100 | 2.1218          | 0.3587 |
| 0.0721        | 97.83  | 2250 | 2.2428          | 0.3519 |
| 0.0742        | 104.35 | 2400 | 2.2293          | 0.3364 |
| 0.0629        | 110.87 | 2550 | 2.2878          | 0.3371 |
| 0.0495        | 117.39 | 2700 | 2.2672          | 0.3408 |
| 0.0466        | 123.91 | 2850 | 2.2532          | 0.3525 |
| 0.0424        | 130.43 | 3000 | 2.2844          | 0.3259 |
| 0.0446        | 136.96 | 3150 | 2.2763          | 0.3253 |
| 0.0411        | 143.48 | 3300 | 2.3011          | 0.3302 |
| 0.0419        | 150.0  | 3450 | 2.3201          | 0.3420 |
| 0.0333        | 156.52 | 3600 | 2.3644          | 0.3439 |
| 0.0384        | 163.04 | 3750 | 2.3685          | 0.3532 |
| 0.0367        | 169.57 | 3900 | 2.3970          | 0.3470 |
| 0.0307        | 176.09 | 4050 | 2.3530          | 0.3309 |
| 0.0328        | 182.61 | 4200 | 2.3415          | 0.3315 |
| 0.0271        | 189.13 | 4350 | 2.4165          | 0.3309 |
| 0.0213        | 195.65 | 4500 | 2.4478          | 0.3451 |
| 0.0193        | 202.17 | 4650 | 2.5241          | 0.3556 |
| 0.0204        | 208.7  | 4800 | 2.5700          | 0.3463 |
| 0.0185        | 215.22 | 4950 | 2.5837          | 0.3178 |
| 0.0161        | 221.74 | 5100 | 2.5139          | 0.3377 |
| 0.0167        | 228.26 | 5250 | 2.5288          | 0.3352 |
| 0.0148        | 234.78 | 5400 | 2.5741          | 0.3389 |
| 0.0141        | 241.3  | 5550 | 2.5174          | 0.3389 |
| 0.0122        | 247.83 | 5700 | 2.5573          | 0.3352 |
| 0.0115        | 254.35 | 5850 | 2.5790          | 0.3296 |
| 0.0141        | 260.87 | 6000 | 2.5774          | 0.3203 |
| 0.0123        | 267.39 | 6150 | 2.6147          | 0.3309 |
| 0.0214        | 273.91 | 6300 | 2.6202          | 0.3302 |
| 0.0107        | 280.43 | 6450 | 2.6264          | 0.3234 |
| 0.0086        | 286.96 | 6600 | 2.6075          | 0.3216 |
| 0.0106        | 293.48 | 6750 | 2.5960          | 0.3247 |
| 0.0085        | 300.0  | 6900 | 2.5952          | 0.3240 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1