Modelpublic

filipesantoscv11/ee63425b-2e55-4109-bd52-6e50f23e2d4b

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

0likes14downloads

Model Card

<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: EleutherAI/pythia-410m-deduped
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 845da76e906c6d62_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/845da76e906c6d62_train_data.json
  type:
    field_instruction: anchor
    field_output: positive
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: filipesantoscv11/ee63425b-2e55-4109-bd52-6e50f23e2d4b
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: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 79GiB
max_steps: 30
micro_batch_size: 4
mlflow_experiment_name: /tmp/845da76e906c6d62_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1e-5
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
sequence_len: 1024
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: b7ee0313-deac-490f-b006-8fa14a2b21c7
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b7ee0313-deac-490f-b006-8fa14a2b21c7
warmup_steps: 5
weight_decay: 0.001
xformers_attention: true

</details><br>

ee63425b-2e55-4109-bd52-6e50f23e2d4b

This model is a fine-tuned version of EleutherAI/pythia-410m-deduped on the None dataset. It achieves the following results on the evaluation set:

—Loss: 2.9647

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: 42
—gradientaccumulationsteps: 4
—totaltrainbatch_size: 16
—optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=adambeta1=0.9,adambeta2=0.95,adam_epsilon=1e-5
—lrschedulertype: cosine
—lrschedulerwarmup_steps: 5
—training_steps: 30

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0048	1	3.1033
10.2719	0.0238	5	3.0752
11.0889	0.0476	10	3.0354
11.6186	0.0713	15	3.0081
11.9721	0.0951	20	2.9806
11.9897	0.1189	25	2.9613
12.4756	0.1427	30	2.9647

Framework versions

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