metadata
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: med-lora/Llama2-Medtext-txt-lora-epochs-2-lr-0001
results: []
See axolotl config
axolotl version: 0.4.0
base_model: meta-llama/Llama-2-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: utrgvseniorproject/medtext-txt
type: completion
dataset_prepared_path: /home/ethensanchez01/med-llm/last_run_prepared
val_set_size: 0.05
output_dir: ./med-lora/Llama2-Medtext-txt-lora-epochs-2-lr-0001
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
wandb_project: Llama2-Medtext-Lora
wandb_entity: utrgvmedai
wandb_watch:
wandb_name: Llama2-Medtext-txt-lora-epochs-2-lr-0001
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0001
train_on_inputs: True # make sure you have this on True
group_by_length: false
bf16: true
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
eval_sample_packing:
save_steps: 800
debug:
deepspeed: /home/ethensanchez01/src/axolotl/deepspeed_configs/zero2.json
weight_decay: 0.001
fsdp:
fsdp_config:
special_tokens:
med-lora/Llama2-Medtext-txt-lora-epochs-2-lr-0001
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4128
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.532 | 0.19 | 1 | 1.4208 |
| 1.5994 | 0.38 | 2 | 1.4210 |
| 1.6281 | 0.76 | 4 | 1.4198 |
| 1.6221 | 1.05 | 6 | 1.4168 |
| 1.5891 | 1.43 | 8 | 1.4136 |
| 1.582 | 1.81 | 10 | 1.4128 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.0