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---
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
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