---
license: apache-2.0
base_model: scb10x/typhoon-7b
tags:
- generated_from_trainer
model-index:
- name: out
  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. -->

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.3.0`
```yaml
base_model: scb10x/typhoon-7b
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: finetune-data.jsonl
    type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./out

sequence_len: 8192
sample_packing: false
pad_to_sequence_len: true
eval_sample_packing: false

wandb_project: typhoon-7b
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.05
evals_per_epoch: 5
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 5
save_total_limit: 10
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

```

</details><br>

# out

This model is a fine-tuned version of [scb10x/typhoon-7b](https://huggingface.co/scb10x/typhoon-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7682

## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 23
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.4821        | 0.0   | 1    | 4.2554          |
| 0.7752        | 0.2   | 48   | 0.7134          |
| 0.7287        | 0.41  | 96   | 0.6403          |
| 0.6135        | 0.61  | 144  | 0.6305          |
| 0.7828        | 0.81  | 192  | 0.6020          |
| 0.3375        | 1.02  | 240  | 0.5951          |
| 0.471         | 1.22  | 288  | 0.6191          |
| 0.2798        | 1.42  | 336  | 0.6249          |
| 0.5071        | 1.63  | 384  | 0.6213          |
| 0.2792        | 1.83  | 432  | 0.6176          |
| 0.069         | 2.03  | 480  | 0.6393          |
| 0.0742        | 2.23  | 528  | 0.6877          |
| 0.1309        | 2.44  | 576  | 0.6892          |
| 0.0349        | 2.64  | 624  | 0.6701          |
| 0.0639        | 2.84  | 672  | 0.6657          |
| 0.0273        | 3.05  | 720  | 0.6895          |
| 0.0311        | 3.25  | 768  | 0.7606          |
| 0.0307        | 3.45  | 816  | 0.7636          |
| 0.0791        | 3.66  | 864  | 0.7664          |
| 0.0747        | 3.86  | 912  | 0.7682          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0