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---
base_model: DewEfresh/neo_7b-slerp
library_name: peft
tags:
- axolotl
- generated_from_trainer
model-index:
- name: neo-7b-slerp-hermes2
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: `0.4.1`
```yaml
adapter: qlora
base_model: DewEfresh/neo_7b-slerp
bf16: auto
chat_template: chatml
dataset_prepared_path: null
datasets:
- conversation: chatml
path: https://huggingface.co/datasets/cognitivecomputations/dolphin-2.9.3/resolve/main/openhermes200k_unfiltered.jsonl
type: sharegpt
debug: null
deepspeed: null
early_stopping_patience: null
eval_sample_packing: false
evals_per_epoch: 3
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: false
hub_model_id: DewEfresh/neo-7b-slerp-hermes2
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules: null
lr_scheduler: cosine
micro_batch_size: 8
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: ./outputs/qlora-out
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 1
sequence_len: 4096
special_tokens: null
strict: false
tf32: false
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_log_model: null
wandb_name: null
wandb_project: neo-7b-slerp-hermes2
wandb_watch: null
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# neo-7b-slerp-hermes2
This model is a fine-tuned version of [DewEfresh/neo_7b-slerp](https://huggingface.co/DewEfresh/neo_7b-slerp) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5603
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 1024
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 15.1348 | 0.0521 | 1 | 14.5242 |
| 9.6676 | 0.3648 | 7 | 8.0894 |
| 7.076 | 0.7296 | 14 | 6.8289 |
| 6.6836 | 1.0717 | 21 | 6.4673 |
| 6.3156 | 1.4365 | 28 | 6.1033 |
| 6.0471 | 1.8013 | 35 | 5.8471 |
| 5.834 | 2.1433 | 42 | 5.6670 |
| 5.7349 | 2.5081 | 49 | 5.5762 |
| 5.7014 | 2.8730 | 56 | 5.5603 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1