---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gopdataset_phonome_base
  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. -->

# gopdataset_phonome_base

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: 0.2722
- Cer: 0.1144

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 10.4672       | 0.84  | 100  | 12.3501         | 0.9750 |
| 5.6053        | 1.68  | 200  | 4.4724          | 0.9750 |
| 3.6779        | 2.52  | 300  | 3.5514          | 0.9750 |
| 3.3108        | 3.36  | 400  | 3.4045          | 0.9750 |
| 3.2684        | 4.2   | 500  | 3.4435          | 0.7828 |
| 3.1223        | 5.04  | 600  | 3.0123          | 0.7864 |
| 2.663         | 5.88  | 700  | 2.1177          | 0.6216 |
| 1.8146        | 6.72  | 800  | 0.9518          | 0.2387 |
| 1.0305        | 7.56  | 900  | 0.5432          | 0.1662 |
| 0.7835        | 8.4   | 1000 | 0.4268          | 0.1500 |
| 0.6468        | 9.24  | 1100 | 0.3911          | 0.1422 |
| 0.564         | 10.08 | 1200 | 0.3544          | 0.1378 |
| 0.5089        | 10.92 | 1300 | 0.3322          | 0.1356 |
| 0.4667        | 11.76 | 1400 | 0.3058          | 0.1277 |
| 0.4304        | 12.61 | 1500 | 0.2984          | 0.1248 |
| 0.4248        | 13.45 | 1600 | 0.3040          | 0.1270 |
| 0.4041        | 14.29 | 1700 | 0.2886          | 0.1223 |
| 0.3641        | 15.13 | 1800 | 0.2860          | 0.1215 |
| 0.3611        | 15.97 | 1900 | 0.2868          | 0.1220 |
| 0.3336        | 16.81 | 2000 | 0.2906          | 0.1217 |
| 0.3329        | 17.65 | 2100 | 0.2908          | 0.1213 |
| 0.3264        | 18.49 | 2200 | 0.2933          | 0.1204 |
| 0.3059        | 19.33 | 2300 | 0.2818          | 0.1193 |
| 0.2966        | 20.17 | 2400 | 0.2924          | 0.1196 |
| 0.2948        | 21.01 | 2500 | 0.2851          | 0.1186 |
| 0.2833        | 21.85 | 2600 | 0.2818          | 0.1181 |
| 0.2724        | 22.69 | 2700 | 0.2884          | 0.1183 |
| 0.2693        | 23.53 | 2800 | 0.2905          | 0.1179 |
| 0.2593        | 24.37 | 2900 | 0.2894          | 0.1184 |
| 0.2515        | 25.21 | 3000 | 0.2931          | 0.1169 |
| 0.2487        | 26.05 | 3100 | 0.2915          | 0.1176 |
| 0.2518        | 26.89 | 3200 | 0.2900          | 0.1176 |
| 0.2467        | 27.73 | 3300 | 0.2934          | 0.1175 |
| 0.246         | 28.57 | 3400 | 0.2965          | 0.1182 |
| 0.2537        | 29.41 | 3500 | 0.2948          | 0.1183 |


### Framework versions

- Transformers 4.17.0
- Pytorch 2.4.0
- Datasets 1.18.3
- Tokenizers 0.20.3