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---
library_name: peft
license: llama3
base_model: scb10x/llama-3-typhoon-v1.5-8b-instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 44b102c7-145e-48d6-9381-9d8e77b9ec37
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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
adapter: lora
base_model: scb10x/llama-3-typhoon-v1.5-8b-instruct
bf16: true
chat_template: llama3
datasets:
- data_files:
- 1cdad3506d86664d_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/1cdad3506d86664d_train_data.json
type:
field_input: input
field_instruction: instruction
field_output: output
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
hub_model_id: lesso05/44b102c7-145e-48d6-9381-9d8e77b9ec37
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 2.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
0: 77GiB
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/1cdad3506d86664d_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 25
save_strategy: steps
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 0c862fee-2042-414b-98c3-2b6c8e57613b
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 0c862fee-2042-414b-98c3-2b6c8e57613b
warmup_steps: 10
weight_decay: 0.01
xformers_attention: false
```
</details><br>
# 44b102c7-145e-48d6-9381-9d8e77b9ec37
This model is a fine-tuned version of [scb10x/llama-3-typhoon-v1.5-8b-instruct](https://huggingface.co/scb10x/llama-3-typhoon-v1.5-8b-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5328
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.4222 | 0.0020 | 1 | 3.3075 |
| 3.1912 | 0.0180 | 9 | 3.0757 |
| 2.4003 | 0.0360 | 18 | 2.2169 |
| 1.7916 | 0.0539 | 27 | 1.7909 |
| 1.7379 | 0.0719 | 36 | 1.7060 |
| 1.586 | 0.0899 | 45 | 1.6494 |
| 1.5214 | 0.1079 | 54 | 1.6072 |
| 1.4854 | 0.1259 | 63 | 1.5724 |
| 1.6245 | 0.1439 | 72 | 1.5498 |
| 1.7521 | 0.1618 | 81 | 1.5376 |
| 1.5649 | 0.1798 | 90 | 1.5333 |
| 1.6523 | 0.1978 | 99 | 1.5328 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1