See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: EleutherAI/gpt-neo-1.3B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 62abd307a8030b27_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/62abd307a8030b27_train_data.json
type:
field_input: intent
field_instruction: instruction
field_output: response
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: 500
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: lesso06/0328ec5c-27b9-4079-bff7-c86aa1fe6b09
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: true
load_in_8bit: true
local_rank: null
logging_steps: 50
lora_alpha: 32
lora_dropout: 0.15
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: 2
mlflow_experiment_name: /tmp/62abd307a8030b27_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
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: 60
sequence_len: 1024
special_tokens:
pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
use_cache: false
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: f6d19dce-e76f-4e7c-a35c-604e0cdb99a9
wandb_project: 06a
wandb_run: your_name
wandb_runid: f6d19dce-e76f-4e7c-a35c-604e0cdb99a9
warmup_steps: 100
weight_decay: 0.01
xformers_attention: true
0328ec5c-27b9-4079-bff7-c86aa1fe6b09
This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6048
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 60
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0000 | 1 | 0.8712 |
2.3986 | 0.0169 | 500 | 0.6048 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Inference Providers
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The model has no pipeline_tag.
Model tree for lesso06/0328ec5c-27b9-4079-bff7-c86aa1fe6b09
Base model
EleutherAI/gpt-neo-1.3B