---
base_model: HKUSTAudio/Llasa-1B
library_name: peft
license: cc-by-nc-4.0
tags:
- generated_from_trainer
model-index:
- name: A10-Llasa-1B_220K
  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. -->

# A10-Llasa-1B_220K

This model is a fine-tuned version of [HKUSTAudio/Llasa-1B](https://huggingface.co/HKUSTAudio/Llasa-1B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.3216

## 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: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| No log        | 0      | 0     | 7.8117          |
| 7.3694        | 0.0089 | 1000  | 7.5275          |
| 7.3694        | 0.0089 | 1000  | 7.5158          |
| 7.0835        | 0.0715 | 2000  | 7.4015          |
| 7.0793        | 0.1072 | 3000  | 7.3785          |
| 7.0461        | 0.1430 | 4000  | 7.3690          |
| 7.0339        | 0.1787 | 5000  | 7.3580          |
| 6.9696        | 0.2144 | 6000  | 7.3513          |
| 7.033         | 0.2502 | 7000  | 7.3444          |
| 6.9768        | 0.2859 | 8000  | 7.3387          |
| 7.1218        | 0.3216 | 9000  | 7.3378          |
| 7.041         | 0.3574 | 10000 | 7.3314          |
| 6.9799        | 0.3931 | 11000 | 7.3350          |
| 7.0261        | 0.4289 | 12000 | 7.3297          |
| 6.888         | 0.4646 | 13000 | 7.3288          |
| 6.9483        | 0.5003 | 14000 | 7.3285          |
| 6.989         | 0.5361 | 15000 | 7.3269          |
| 7.0167        | 0.5718 | 16000 | 7.3243          |
| 6.9611        | 0.6076 | 17000 | 7.3273          |
| 6.9077        | 0.6433 | 18000 | 7.3256          |
| 7.0845        | 0.6790 | 19000 | 7.3235          |
| 6.8593        | 0.7148 | 20000 | 7.3207          |
| 6.8621        | 0.7505 | 21000 | 7.3216          |
| 7.1707        | 0.7863 | 22000 | 7.3225          |
| 6.9153        | 0.8220 | 23000 | 7.3209          |
| 6.9139        | 0.8577 | 24000 | 7.3217          |
| 6.9           | 0.8935 | 25000 | 7.3214          |
| 6.7397        | 0.9292 | 26000 | 7.3207          |
| 6.9967        | 0.9649 | 27000 | 7.3216          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1