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: vicgalle/alpaca-gpt4
type: alpaca
conversations: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: ./outputs/out_llama2_alpaca
hub_model_id: flydust/Llama-2-7b-Alpaca52k-GPT4
sequence_len: 4096
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 2e-5
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
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
warmup_ratio: 0.03
evals_per_epoch: 3
eval_table_size:
saves_per_epoch: 1
debug:
weight_decay: 0.
fsdp:
fsdp_config:
special_tokens:
Llama-2-7b-Alpaca52k-GPT4
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: 0.7849
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_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 |
|---|---|---|---|
| 1.0592 | 0.0111 | 1 | 1.1104 |
| 0.8995 | 0.3343 | 30 | 0.8043 |
| 0.8809 | 0.6685 | 60 | 0.7920 |
| 0.8642 | 1.0028 | 90 | 0.7868 |
| 0.8402 | 1.3231 | 120 | 0.7844 |
| 0.8093 | 1.6574 | 150 | 0.7841 |
| 0.8071 | 1.9916 | 180 | 0.7804 |
| 0.7532 | 2.3120 | 210 | 0.7853 |
| 0.7667 | 2.6462 | 240 | 0.7844 |
| 0.7555 | 2.9805 | 270 | 0.7836 |
| 0.7569 | 3.3008 | 300 | 0.7851 |
| 0.7634 | 3.6351 | 330 | 0.7849 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for flydust/Llama-2-7b-Alpaca52k-GPT4
Base model
meta-llama/Llama-2-7b-hf