---
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