File size: 1,903 Bytes
fdba5d6
 
c6cd5ac
 
 
 
 
 
fdba5d6
 
c6cd5ac
 
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
 
e764563
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
 
 
 
 
 
 
 
 
 
 
fdba5d6
c6cd5ac
fdba5d6
c6cd5ac
 
e764563
 
 
 
 
 
 
 
 
 
fdba5d6
 
c6cd5ac
fdba5d6
c6cd5ac
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
---
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