File size: 2,719 Bytes
ce5a5b8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
60891c9
ce5a5b8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
60891c9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ce5a5b8
 
 
 
 
 
 
 
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
71
72
73
74
75
76
77
78
79
80
81
82
83
84
---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM-135M
tags:
- generated_from_trainer
model-index:
- name: distily_smollm_dataset_sweep
  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. -->

# distily_smollm_dataset_sweep

This model is a fine-tuned version of [HuggingFaceTB/SmolLM-135M](https://huggingface.co/HuggingFaceTB/SmolLM-135M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2647

## 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step   | Validation Loss |
|:-------------:|:------:|:------:|:---------------:|
| No log        | 0      | 0      | 18.8388         |
| 1.2041        | 0.0401 | 5000   | 1.1584          |
| 0.7528        | 0.0802 | 10000  | 0.7396          |
| 0.5961        | 0.1202 | 15000  | 0.6070          |
| 0.5023        | 0.1603 | 20000  | 0.5307          |
| 0.4706        | 0.2004 | 25000  | 0.4836          |
| 0.4605        | 0.2405 | 30000  | 0.4512          |
| 0.417         | 0.2806 | 35000  | 0.4251          |
| 0.4027        | 0.3206 | 40000  | 0.4071          |
| 0.3693        | 0.3607 | 45000  | 0.3898          |
| 0.3745        | 0.4008 | 50000  | 0.3759          |
| 0.3652        | 0.4409 | 55000  | 0.3632          |
| 0.3537        | 0.4810 | 60000  | 0.3529          |
| 0.3665        | 0.5210 | 65000  | 0.3440          |
| 0.3177        | 0.5611 | 70000  | 0.3346          |
| 0.3102        | 0.6012 | 75000  | 0.3269          |
| 0.3023        | 0.6413 | 80000  | 0.3198          |
| 0.3076        | 0.6814 | 85000  | 0.3125          |
| 0.3388        | 0.7214 | 90000  | 0.3062          |
| 0.298         | 0.7615 | 95000  | 0.3003          |
| 0.3052        | 0.8016 | 100000 | 0.2941          |
| 0.2678        | 0.8417 | 105000 | 0.2880          |
| 0.2684        | 0.8818 | 110000 | 0.2824          |
| 0.274         | 0.9218 | 115000 | 0.2764          |
| 0.2647        | 0.9619 | 120000 | 0.2706          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.5.0.dev20240910+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1