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---
library_name: transformers
base_model: ccore/ccore-v3
tags:
- generated_from_trainer
model-index:
- name: ccore-v3
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. -->
# ccore-v3
This model is a fine-tuned version of [ccore/ccore-v3](https://huggingface.co/ccore/ccore-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5452
## 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: 24
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 192
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 1.0 | 15 | 0.5351 |
| No log | 2.0 | 30 | 0.5292 |
| No log | 3.0 | 45 | 0.5297 |
| No log | 4.0 | 60 | 0.5342 |
| No log | 5.0 | 75 | 0.5368 |
| No log | 6.0 | 90 | 0.5420 |
| No log | 7.0 | 105 | 0.5422 |
| No log | 8.0 | 120 | 0.5438 |
| No log | 9.0 | 135 | 0.5452 |
| No log | 9.3540 | 140 | 0.5452 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|