Magpie's Friends
Collection
Collection of baselines!
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9 items
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Updated
axolotl version: 0.4.1
base_model: meta-llama/Meta-Llama-3-8B
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
chat_template: llama3
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: Magpie-Align/Llama-3-8B-Self-Instruct-100K
type: sharegpt
conversation: llama3
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: axolotl_out/Llama-3-8B-self-instruct-100K
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
wandb_project: SynDa
wandb_entity:
wandb_watch:
wandb_name: Llama-3-8B-Self-Instruct
wandb_log_model:
hub_model_id: Magpie-Align/Llama-3-8B-Self-Instruct-100K
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 5
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
pad_token: <|end_of_text|>
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the Magpie-Align/Llama-3-8B-Self-Instruct-100K dataset. It achieves the following results on the evaluation set:
The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3442 | 0.0190 | 1 | 2.3110 |
0.9581 | 0.2095 | 11 | 1.1476 |
0.8258 | 0.4190 | 22 | 0.9256 |
0.717 | 0.6286 | 33 | 0.7341 |
0.6746 | 0.8381 | 44 | 0.6497 |
0.5601 | 1.0333 | 55 | 0.6268 |
0.5571 | 1.2429 | 66 | 0.6285 |
0.538 | 1.4524 | 77 | 0.6258 |
0.548 | 1.6619 | 88 | 0.6251 |
0.5467 | 1.8714 | 99 | 0.6245 |
Base model
meta-llama/Meta-Llama-3-8B