File size: 1,770 Bytes
55a9e2d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: peft
license: cc-by-nc-4.0
base_model: facebook/musicgen-small
tags:
- generated_from_trainer
model-index:
- name: salami_truncsplit_finetune_model_16
  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. -->

# salami_truncsplit_finetune_model_16

This model is a fine-tuned version of [facebook/musicgen-small](https://huggingface.co/facebook/musicgen-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7648
- Clap: 0.2037

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 456
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.99) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Clap   |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 9.2964        | 0.2407 | 25   | 3.6824          | 0.2393 |
| 8.452         | 0.4813 | 50   | 3.7090          | 0.2203 |
| 8.2681        | 0.7220 | 75   | 3.7505          | 0.1934 |
| 8.0758        | 0.9627 | 100  | 3.7648          | 0.2037 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.47.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3