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empower-dev-staging/empower-functions-small-v1-1-lc-2

sourceHugging Facellama3updated 2y agoView on Hugging Face
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Model Card

<!-- 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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>

axolotl version: 0.4.1

yaml
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

chat_template: llama3

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
- path: ./hf_data/function_not_used_no_unicode_7500.jsonl
  type: sharegpt
  conversation: llama-3
- path: ./hf_data/function_used_training_shuffled_no_unicode_without_examples_corrected_updated.jsonl
  type: sharegpt
  conversation: llama-3
- path: ./hf_data/parallel_data_training_no_unicode_updated.jsonl
  type: sharegpt
  conversation: llama-3
- path: ./hf_data/parallel_data_training_single_function.jsonl  
  type: sharegpt
  conversation: llama-3   
- path: ./hf_data/function_not_used_new.jsonl
  type: sharegpt
  conversation: llama-3   
- path: ./hf_data/lambda_dataset_100.jsonl
  type: sharegpt
  conversation: llama-3  
- path: ./hf_data/function_not_used_new_more.jsonl
  type: sharegpt
  conversation: llama-3

dataset_prepared_path: last_run_prepared
val_set_size: 0.025

output_dir: ../empower-functions-llama3-1-8b-with-more-neg-5

hub_model_id: empower-dev-staging/empower-functions-llama3-1-8b-with-more-neg-5
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

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
s2_attention:

warmup_steps: 10

eval_batch_size: 2
eval_max_new_tokens: 256
eval_steps: 0.1
eval_table_size: null

saves_per_epoch: 4

debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
   pad_token: <|end_of_text|>

</details><br>

empower-functions-llama3-1-8b-with-more-neg-5

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0968

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
  • —trainbatchsize: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 2
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 16
  • —totalevalbatch_size: 4
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 10
  • —num_epochs: 1

Training results

Training LossEpochStepValidation Loss
0.99910.003310.9484
0.19140.1016310.1566
0.15630.2033620.1268
0.05980.3049930.1189
0.09360.40661240.1115
0.09260.50821550.1067
0.08290.60981860.1024
0.12670.71152170.0996
0.08270.81312480.0978
0.09910.91482790.0968

Framework versions

  • —PEFT 0.12.0
  • —Transformers 4.44.0
  • —Pytorch 2.3.0+cu121
  • —Datasets 2.20.0
  • —Tokenizers 0.19.1