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library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
model-index:
- name: w2v-bert-2.0-gui
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. -->
# w2v-bert-2.0-gui
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9872
- Cer: 0.9839
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 20.5172 | 0.4329 | 100 | 6.1927 | 1.0 |
| 9.1755 | 0.8658 | 200 | 3.0737 | 1.0 |
| 5.9769 | 1.2987 | 300 | 2.9275 | 0.9839 |
| 5.8767 | 1.7316 | 400 | 2.9258 | 0.9839 |
| 6.0773 | 2.1645 | 500 | 2.9087 | 0.9839 |
| 5.9225 | 2.5974 | 600 | 2.9052 | 0.9839 |
| 5.9328 | 3.0303 | 700 | 2.9009 | 0.9839 |
| 5.8895 | 3.4632 | 800 | 2.8969 | 0.9368 |
| 5.8888 | 3.8961 | 900 | 2.9218 | 0.9839 |
| 5.9117 | 4.3290 | 1000 | 2.9595 | 0.9672 |
| 5.9625 | 4.7619 | 1100 | 2.9033 | 0.9839 |
| 6.0566 | 5.1948 | 1200 | 2.9598 | 0.9839 |
| 5.9214 | 5.6277 | 1300 | 2.9107 | 0.9839 |
| 5.9976 | 6.0606 | 1400 | 2.9289 | 0.9839 |
| 5.9904 | 6.4935 | 1500 | 2.9166 | 0.9839 |
| 5.9354 | 6.9264 | 1600 | 2.9257 | 0.9839 |
| 6.0097 | 7.3593 | 1700 | 2.9428 | 0.9839 |
| 6.0392 | 7.7922 | 1800 | 2.9378 | 0.9839 |
| 5.9639 | 8.2251 | 1900 | 2.9657 | 0.9839 |
| 6.0595 | 8.6580 | 2000 | 2.9771 | 0.9839 |
| 6.0797 | 9.0909 | 2100 | 2.9865 | 0.9839 |
| 6.0741 | 9.5238 | 2200 | 2.9870 | 0.9839 |
| 6.0342 | 9.9567 | 2300 | 2.9872 | 0.9839 |
### Framework versions
- Transformers 5.1.0
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2
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