---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gopdataset_phonome_base_add_transformer
  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_add_transformer

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: 0.3081
- Cer: 0.1141

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.7266        | 0.84  | 100  | 3.4268          | 0.9750 |
| 3.258         | 1.68  | 200  | 3.2266          | 0.7902 |
| 2.5421        | 2.52  | 300  | 1.1589          | 0.5124 |
| 1.0681        | 3.36  | 400  | 0.4367          | 0.1676 |
| 0.7192        | 4.2   | 500  | 0.4418          | 0.1658 |
| 0.5793        | 5.04  | 600  | 0.3079          | 0.1331 |
| 0.5329        | 5.88  | 700  | 0.3078          | 0.1287 |
| 0.4988        | 6.72  | 800  | 0.3051          | 0.1251 |
| 0.4455        | 7.56  | 900  | 0.2843          | 0.1206 |
| 0.4271        | 8.4   | 1000 | 0.2865          | 0.1234 |
| 0.4027        | 9.24  | 1100 | 0.2996          | 0.1214 |
| 0.3939        | 10.08 | 1200 | 0.2874          | 0.1199 |
| 0.3633        | 10.92 | 1300 | 0.2777          | 0.1237 |
| 0.3482        | 11.76 | 1400 | 0.2648          | 0.1171 |
| 0.3267        | 12.61 | 1500 | 0.2737          | 0.1174 |
| 0.3334        | 13.45 | 1600 | 0.2812          | 0.1176 |
| 0.3145        | 14.29 | 1700 | 0.2709          | 0.1163 |
| 0.2921        | 15.13 | 1800 | 0.2689          | 0.1153 |
| 0.2939        | 15.97 | 1900 | 0.2757          | 0.1153 |
| 0.2681        | 16.81 | 2000 | 0.2785          | 0.1161 |
| 0.2691        | 17.65 | 2100 | 0.2955          | 0.1196 |
| 0.2627        | 18.49 | 2200 | 0.2922          | 0.1174 |
| 0.2519        | 19.33 | 2300 | 0.2820          | 0.1148 |
| 0.2391        | 20.17 | 2400 | 0.3038          | 0.1190 |
| 0.2393        | 21.01 | 2500 | 0.2873          | 0.1162 |
| 0.2324        | 21.85 | 2600 | 0.2903          | 0.1148 |
| 0.2217        | 22.69 | 2700 | 0.3018          | 0.1167 |
| 0.2156        | 23.53 | 2800 | 0.3033          | 0.1153 |
| 0.2039        | 24.37 | 2900 | 0.2975          | 0.1147 |
| 0.2018        | 25.21 | 3000 | 0.3055          | 0.1159 |
| 0.1996        | 26.05 | 3100 | 0.3035          | 0.1151 |
| 0.2013        | 26.89 | 3200 | 0.3032          | 0.1153 |
| 0.2002        | 27.73 | 3300 | 0.3029          | 0.1146 |
| 0.196         | 28.57 | 3400 | 0.3118          | 0.1157 |
| 0.2047        | 29.41 | 3500 | 0.3081          | 0.1141 |


### Framework versions

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