File size: 1,562 Bytes
a47cafa
9512d6b
 
 
 
 
a47cafa
 
9512d6b
 
a47cafa
9512d6b
a47cafa
9512d6b
 
ef12c09
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
a47cafa
9512d6b
 
 
 
 
 
 
 
 
 
 
 
 
ef12c09
a47cafa
9512d6b
a47cafa
ef12c09
 
 
 
 
 
 
a47cafa
 
9512d6b
a47cafa
9512d6b
 
 
 
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
---
tags:
- generated_from_trainer
model-index:
- name: mistral-7b-peptide-v4
  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. -->

# mistral-7b-peptide-v4

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3129

## 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: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1359        | 0.2   | 100  | 0.1768          |
| 0.0804        | 0.4   | 200  | 0.2530          |
| 0.0573        | 0.6   | 300  | 0.2863          |
| 0.0415        | 0.8   | 400  | 0.3172          |
| 0.0422        | 1.0   | 500  | 0.3129          |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1