---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
training_config:
  vocab_size: 30000
  hidden_size: 256
  intermediate_size: 1024
  num_hidden_layers: 6
  num_attention_heads: 4
  num_key_value_heads: 4
  sliding_window: 256
  max_position_embeddings: 4096
  pad_token_id: 0
  bos_token_id: 1
  eos_token_id: 2
pipeline_tag: other
model-index:
- name: OKAI-midi-gen-v-004
  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. -->

# OKAI-midi-gen-v-004

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 10.2911
- Accuracy: 0.0003

## 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: 16
- seed: 444
- gradient_accumulation_steps: 3
- total_train_batch_size: 24
- 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_with_restarts
- lr_scheduler_warmup_ratio: 0.3
- training_steps: 2000

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 10.2092       | 3.2283  | 100  | 10.2764         | 0.0004   |
| 9.7373        | 6.4565  | 200  | 10.0773         | 0.0020   |
| 9.2158        | 9.6848  | 300  | 9.9404          | 0.0023   |
| 8.8101        | 12.9130 | 400  | 9.9445          | 0.0027   |
| 8.3439        | 16.1304 | 500  | 9.9546          | 0.0016   |
| 7.7001        | 19.3587 | 600  | 9.9316          | 0.0012   |
| 6.9652        | 22.5870 | 700  | 9.9396          | 0.0007   |
| 6.2067        | 25.8152 | 800  | 9.9274          | 0.0007   |
| 5.5185        | 29.0326 | 900  | 9.9435          | 0.0007   |
| 4.8318        | 32.2609 | 1000 | 9.9918          | 0.0004   |
| 4.343         | 35.4891 | 1100 | 10.0255         | 0.0004   |
| 3.9477        | 38.7174 | 1200 | 10.0792         | 0.0004   |
| 3.5394        | 41.9457 | 1300 | 10.1247         | 0.0002   |
| 3.2964        | 45.1630 | 1400 | 10.1824         | 0.0003   |
| 3.0237        | 48.3913 | 1500 | 10.2247         | 0.0003   |
| 2.8621        | 51.6196 | 1600 | 10.2556         | 0.0003   |
| 2.765         | 54.8478 | 1700 | 10.2756         | 0.0001   |
| 2.7383        | 58.0652 | 1800 | 10.2867         | 0.0003   |
| 2.7324        | 61.2935 | 1900 | 10.2906         | 0.0003   |
| 2.6918        | 64.5217 | 2000 | 10.2911         | 0.0003   |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.6.0
- Datasets 3.6.0
- Tokenizers 0.21.1