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---
license: llama3
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
model-index:
- name: llama3-8b-hermes-sandals-sample-10k
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: `0.4.0`
```yaml
base_model: meta-llama/Meta-Llama-3-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: ./data/openhermes2_5_10k.jsonl
type: sharegpt
conversation: chatml
dataset_prepared_path:
val_set_size: 0.15
output_dir: ./lora-output-dir
hub_model_id: venetis/llama3-8b-hermes-sandals-sample-10k
data_seed: 117
seed: 117
chat_template: chatml
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
sequence_len: 4096
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true
wandb_project: llama-3-8b-hermes-sandals-sample-10k
wandb_entity: venetispall
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 2e-4
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
#UPDATES mk2 - added special tokens
special_tokens:
eos_token: "<|im_end|>"
pad_token: "<|end_of_text|>"
tokens:
- "<|im_start|>"
- "<|im_end|>"
lora_modules_to_save:
- embed_tokens
- lm_head
```
</details><br>
# llama3-8b-hermes-sandals-sample-10k
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8913
## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 117
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9567 | 0.0102 | 1 | 1.0036 |
| 0.7583 | 0.2545 | 25 | 0.8184 |
| 0.8226 | 0.5089 | 50 | 0.8238 |
| 0.7471 | 0.7634 | 75 | 0.8094 |
| 0.7339 | 1.0178 | 100 | 0.7954 |
| 0.4737 | 1.2494 | 125 | 0.8393 |
| 0.4723 | 1.5038 | 150 | 0.8395 |
| 0.5529 | 1.7583 | 175 | 0.8327 |
| 0.4288 | 2.0127 | 200 | 0.8277 |
| 0.2476 | 2.2468 | 225 | 0.8617 |
| 0.2566 | 2.5013 | 250 | 0.8676 |
| 0.2787 | 2.7557 | 275 | 0.8654 |
| 0.3477 | 3.0102 | 300 | 0.8648 |
| 0.1912 | 3.2392 | 325 | 0.8909 |
| 0.1868 | 3.4936 | 350 | 0.8912 |
| 0.1864 | 3.7481 | 375 | 0.8913 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1 |