metadata
library_name: peft
license: apache-2.0
base_model: JackFram/llama-160m
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 43add8cb-08d4-4521-abc0-1167226993fa
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: JackFram/llama-160m
bf16: true
chat_template: llama3
datasets:
- data_files:
- 2b85bbf48041fd87_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/2b85bbf48041fd87_train_data.json
type:
field_input: poem_verses
field_instruction: poem_title
field_output: poem_theme
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: 2
gradient_checkpointing: true
group_by_length: false
hub_model_id: lesso04/43add8cb-08d4-4521-abc0-1167226993fa
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
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: 77GiB
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/2b85bbf48041fd87_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
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: 25
save_strategy: steps
sequence_len: 1024
special_tokens:
pad_token: </s>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 43add8cb-08d4-4521-abc0-1167226993fa
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 43add8cb-08d4-4521-abc0-1167226993fa
warmup_steps: 10
weight_decay: 0.01
xformers_attention: false
43add8cb-08d4-4521-abc0-1167226993fa
This model is a fine-tuned version of JackFram/llama-160m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2620
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.7383 | 0.0019 | 1 | 4.8211 |
| 4.0801 | 0.0175 | 9 | 3.9355 |
| 2.2625 | 0.0349 | 18 | 2.1969 |
| 1.1658 | 0.0524 | 27 | 1.3317 |
| 0.8439 | 0.0698 | 36 | 0.8822 |
| 0.5331 | 0.0873 | 45 | 0.6151 |
| 0.5796 | 0.1048 | 54 | 0.4402 |
| 0.4189 | 0.1222 | 63 | 0.3443 |
| 0.25 | 0.1397 | 72 | 0.3007 |
| 0.1978 | 0.1571 | 81 | 0.2723 |
| 0.3042 | 0.1746 | 90 | 0.2629 |
| 0.2709 | 0.1920 | 99 | 0.2620 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1