File size: 2,297 Bytes
1ad20a2
3919e78
 
38cdd62
3919e78
 
 
38cdd62
 
0c87131
94a54b4
 
1ad20a2
3919e78
 
 
 
 
 
0c87131
 
 
3919e78
0c8ac94
 
 
3919e78
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
722c8d0
3919e78
 
 
 
 
 
722c8d0
0c8ac94
 
3919e78
 
 
 
722c8d0
3919e78
 
 
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
---
tags:
- generated_from_keras_callback
- music
model-index:
- name: juancopi81/mutopia_guitar_mmm
  results: []
datasets:
- juancopi81/mutopia_guitar_dataset
widget:
- text: "PIECE_START TIME_SIGNATURE=4_4 BPM=90 TRACK_START INST=0 DENSITY=2 BAR_START NOTE_ON=43"
  example_title: "Time signature 4/4, BPM=90, NOTE=G2"
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# juancopi81/mutopia_guitar_mmm

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the [Mutopia Guitar Dataset](https://huggingface.co/datasets/juancopi81/mutopia_guitar_dataset). Use the widget to generate your piece and then use [this notebook](https://colab.research.google.com/drive/14vlJwCvDmNH6SFfVuYY0Y18qTbaHEJCY?usp=sharing) to hear it (work in progress). 
The notebook is adapted from [the one created by Dr. Tristan Behrens](https://huggingface.co/TristanBehrens/js-fakes-4bars).

It achieves the following results on the evaluation set:
- Train Loss: 0.7588
- Validation Loss: 1.3974
- Epoch: 2

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 9089, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.0705     | 1.3590          | 0     |
| 0.8889     | 1.3702          | 1     |
| 0.7588     | 1.3974          | 2     |


### Framework versions

- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1