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---
library_name: transformers
license: apache-2.0
base_model: dandelin/vilt-b32-mlm
tags:
- generated_from_trainer
model-index:
- name: results2
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. -->
# results2
This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-mlm) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 54.5580
- Bleu Score: {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304}
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu Score |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| 620.8193 | 1.0 | 63 | 177.3467 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304} |
| 140.721 | 2.0 | 126 | 65.7476 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304} |
| 60.0697 | 3.0 | 189 | 54.5580 | {'bleu': 0.0, 'precisions': [0.0, 0.0, 0.0, 0.0], 'brevity_penalty': 5.701223175160721e-08, 'length_ratio': 0.05656108597285068, 'translation_length': 300, 'reference_length': 5304} |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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