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Rodo-Sami/
ea95758b-5b89-47fe-849a-4d786b885646

Name: ea95758b-5b89-47fe-849a-4d786b885646
Availability: InStock

generated_from_trainer

EleutherAI/gpt-neo-125m

adapter

mit

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See axolotl config

axolotl version: 0.6.0

yaml

adapter: lora
base_model: EleutherAI/gpt-neo-125m
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 9f4a3a5e09185fe6_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/9f4a3a5e09185fe6_train_data.json
  type:
    field_input: document_description
    field_instruction: document_type
    field_output: generated_text
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: false
group_by_length: true
hub_model_id: Rodo-Sami/ea95758b-5b89-47fe-849a-4d786b885646
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: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 1500
micro_batch_size: 2
mlflow_experiment_name: /tmp/9f4a3a5e09185fe6_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
special_tokens:
  pad_token: <|endoftext|>
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: offline
wandb_name: 9668f134-f5af-4223-a8e9-dd5d58ae281f
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 9668f134-f5af-4223-a8e9-dd5d58ae281f
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

ea95758b-5b89-47fe-849a-4d786b885646

This model is a fine-tuned version of EleutherAI/gpt-neo-125m on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.0257

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
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Use adamw_bnb_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10
training_steps: 1500

Training results

Training Loss	Epoch	Step	Validation Loss
2.0411	0.2266	375	2.1331
3.7391	0.4532	750	2.0589
1.9296	0.6798	1125	2.0308
3.5514	0.9064	1500	2.0257

Framework versions

PEFT 0.14.0
Transformers 4.46.3
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3