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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gopdataset_base_fadam
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_base_fadam
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1001
- Wer: 0.1662
## 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: 8
- 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 | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.9033 | 1.05 | 500 | 3.0006 | 1.0 |
| 2.1655 | 2.11 | 1000 | 0.3024 | 0.3575 |
| 0.582 | 3.16 | 1500 | 0.2045 | 0.2566 |
| 0.3618 | 4.21 | 2000 | 0.1377 | 0.2188 |
| 0.3297 | 5.26 | 2500 | 0.1551 | 0.2232 |
| 0.2847 | 6.32 | 3000 | 0.1742 | 0.2486 |
| 0.2488 | 7.37 | 3500 | 0.2328 | 0.2036 |
| 0.1996 | 8.42 | 4000 | 0.1379 | 0.2079 |
| 0.2165 | 9.47 | 4500 | 0.1183 | 0.1924 |
| 0.189 | 10.53 | 5000 | 0.1295 | 0.1956 |
| 0.1817 | 11.58 | 5500 | 0.1198 | 0.1888 |
| 0.1682 | 12.63 | 6000 | 0.1270 | 0.1887 |
| 0.1246 | 13.68 | 6500 | 0.1211 | 0.1867 |
| 0.1442 | 14.74 | 7000 | 0.1301 | 0.1805 |
| 0.1732 | 15.79 | 7500 | 0.1107 | 0.1801 |
| 0.1142 | 16.84 | 8000 | 0.1096 | 0.1848 |
| 0.1485 | 17.89 | 8500 | 0.1075 | 0.1790 |
| 0.1037 | 18.95 | 9000 | 0.1109 | 0.1778 |
| 0.1155 | 20.0 | 9500 | 0.1120 | 0.1736 |
| 0.1162 | 21.05 | 10000 | 0.1053 | 0.1740 |
| 0.0874 | 22.11 | 10500 | 0.1157 | 0.1739 |
| 0.0797 | 23.16 | 11000 | 0.1128 | 0.1735 |
| 0.0726 | 24.21 | 11500 | 0.1089 | 0.1745 |
| 0.0691 | 25.26 | 12000 | 0.1084 | 0.1696 |
| 0.0677 | 26.32 | 12500 | 0.1059 | 0.1696 |
| 0.0582 | 27.37 | 13000 | 0.1065 | 0.1696 |
| 0.0669 | 28.42 | 13500 | 0.1001 | 0.1701 |
| 0.0956 | 29.47 | 14000 | 0.1017 | 0.1687 |
### Framework versions
- Transformers 4.17.0
- Pytorch 2.5.1+cu121
- Datasets 1.18.3
- Tokenizers 0.20.3
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