CoolFace
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rayonlabs/7b9e0afb-6c87-44af-b513-07c5c35cc3f3-614edd8c20080086_dataset_json_X-Amz-Algorithm_AWS4-HMAC-SHA

sourceHugging Faceupdated 1y 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
adapter: lora
base_model: samoline/7b9e0afb-6c87-44af-b513-07c5c35cc3f3
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 44e538a0e30dcde3_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/44e538a0e30dcde3_train_data.json
  type:
    field_input: input
    field_instruction: instruction
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: 250
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: true
hub_model_id: Lin2es/84b33098-74ee-4c1e-9de8-ff0a888e1cd8
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
lora_alpha: 32
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/44e538a0e30dcde3_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 500
saves_per_epoch: null
seed: 1001
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 4ecc76b5-93e3-47f8-96f6-146713475671
wandb_project: text01
wandb_run: your_name
wandb_runid: 4ecc76b5-93e3-47f8-96f6-146713475671
warmup_steps: 100
weight_decay: 0.0
xformers_attention: null

</details><br>

84b33098-74ee-4c1e-9de8-ff0a888e1cd8

This model is a fine-tuned version of samoline/7b9e0afb-6c87-44af-b513-07c5c35cc3f3 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6403

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: 4
  • —evalbatchsize: 4
  • —seed: 1001
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 128
  • —totalevalbatch_size: 16
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 100
  • —training_steps: 500

Training results

Training LossEpochStepValidation Loss
No log0.000910.6493
0.6810.22882500.6440
0.67020.45765000.6403

Framework versions

  • —PEFT 0.13.2
  • —Transformers 4.46.0
  • —Pytorch 2.5.0+cu124
  • —Datasets 3.0.1
  • —Tokenizers 0.20.1