neo-7b-slerp-hermes2

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<details><summary>See axolotl config</summary>

axolotl version: 0.4.1

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 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

Framework versions

• PEFT 0.11.1
• Transformers 4.41.1
• Pytorch 2.1.2+cu118
• Datasets 2.19.1
• Tokenizers 0.19.1