---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-a-nomi
  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. -->

# xlsr-a-nomi

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3688
- Wer: 0.3324

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use 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: 132
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.7382        | 2.2727  | 200  | 2.5107          | 1.0    |
| 1.3613        | 4.5455  | 400  | 0.3782          | 0.5943 |
| 0.2498        | 6.8182  | 600  | 0.2562          | 0.4209 |
| 0.1205        | 9.0909  | 800  | 0.2575          | 0.3548 |
| 0.0772        | 11.3636 | 1000 | 0.2902          | 0.3432 |
| 0.0625        | 13.6364 | 1200 | 0.3199          | 0.3458 |
| 0.0461        | 15.9091 | 1400 | 0.2814          | 0.3351 |
| 0.0348        | 18.1818 | 1600 | 0.3389          | 0.3396 |
| 0.0323        | 20.4545 | 1800 | 0.3000          | 0.3423 |
| 0.0341        | 22.7273 | 2000 | 0.3097          | 0.3342 |
| 0.0271        | 25.0    | 2200 | 0.3270          | 0.3342 |
| 0.0236        | 27.2727 | 2400 | 0.3370          | 0.3423 |
| 0.0245        | 29.5455 | 2600 | 0.3201          | 0.3387 |
| 0.0143        | 31.8182 | 2800 | 0.3483          | 0.3315 |
| 0.0183        | 34.0909 | 3000 | 0.3245          | 0.3333 |
| 0.0149        | 36.3636 | 3200 | 0.3269          | 0.3342 |
| 0.0128        | 38.6364 | 3400 | 0.3180          | 0.3324 |
| 0.0121        | 40.9091 | 3600 | 0.3465          | 0.3387 |
| 0.0145        | 43.1818 | 3800 | 0.3465          | 0.3378 |
| 0.014         | 45.4545 | 4000 | 0.3181          | 0.3342 |
| 0.0101        | 47.7273 | 4200 | 0.3438          | 0.3333 |
| 0.0057        | 50.0    | 4400 | 0.3405          | 0.3387 |
| 0.0101        | 52.2727 | 4600 | 0.3508          | 0.3396 |
| 0.0084        | 54.5455 | 4800 | 0.3602          | 0.3360 |
| 0.0057        | 56.8182 | 5000 | 0.3369          | 0.3378 |
| 0.0143        | 59.0909 | 5200 | 0.3584          | 0.3387 |
| 0.0062        | 61.3636 | 5400 | 0.3748          | 0.3360 |
| 0.0068        | 63.6364 | 5600 | 0.3625          | 0.3369 |
| 0.006         | 65.9091 | 5800 | 0.3773          | 0.3369 |
| 0.0059        | 68.1818 | 6000 | 0.3666          | 0.3351 |
| 0.008         | 70.4545 | 6200 | 0.3597          | 0.3378 |
| 0.0061        | 72.7273 | 6400 | 0.3703          | 0.3396 |
| 0.0041        | 75.0    | 6600 | 0.3843          | 0.3387 |
| 0.0055        | 77.2727 | 6800 | 0.3829          | 0.3360 |
| 0.0028        | 79.5455 | 7000 | 0.3877          | 0.3378 |
| 0.0025        | 81.8182 | 7200 | 0.3898          | 0.3333 |
| 0.0021        | 84.0909 | 7400 | 0.3910          | 0.3342 |
| 0.0021        | 86.3636 | 7600 | 0.3889          | 0.3360 |
| 0.0025        | 88.6364 | 7800 | 0.3871          | 0.3342 |
| 0.0025        | 90.9091 | 8000 | 0.3787          | 0.3333 |
| 0.0016        | 93.1818 | 8200 | 0.3676          | 0.3307 |
| 0.0017        | 95.4545 | 8400 | 0.3651          | 0.3307 |
| 0.0015        | 97.7273 | 8600 | 0.3685          | 0.3324 |
| 0.0015        | 100.0   | 8800 | 0.3688          | 0.3324 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0