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Alphatao/633e6a49-81e3-4492-8a1e-32975c89d1a4
633e6a49-81e3-4492-8a1e-32975c89d1a4 is a machine learning model from Alphatao. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: EleutherAI/gpt-neo-1.3B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- c8397f45edf002b3_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/c8397f45edf002b3_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
device_map:
? ''
: 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: false
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/633e6a49-81e3-4492-8a1e-32975c89d1a4
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
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
lora_target_modules: null
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 2652
micro_batch_size: 4
mlflow_experiment_name: /tmp/c8397f45edf002b3_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
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: 0.04
wandb_entity: null
wandb_mode: online
wandb_name: 7bee0287-1da9-4e6d-9b18-0f8342b3f344
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 7bee0287-1da9-4e6d-9b18-0f8342b3f344
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
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:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 28.7921 | 0.0007 | 1 | 3.6046 |
| 19.3797 | 0.0654 | 100 | 2.4536 |
| 16.8527 | 0.1308 | 200 | 2.2399 |
| 18.0205 | 0.1962 | 300 | 2.1347 |
| 16.2049 | 0.2616 | 400 | 2.0673 |
| 15.984 | 0.3270 | 500 | 2.0087 |
| 15.9218 | 0.3924 | 600 | 1.9615 |
| 15.4433 | 0.4579 | 700 | 1.9172 |
| 16.0857 | 0.5233 | 800 | 1.8853 |
| 15.2135 | 0.5887 | 900 | 1.8540 |
| 13.9709 | 0.6541 | 1000 | 1.8281 |
| 14.4289 | 0.7195 | 1100 | 1.8007 |
| 13.6533 | 0.7849 | 1200 | 1.7801 |
| 13.114 | 0.8503 | 1300 | 1.7613 |
| 13.2745 | 0.9157 | 1400 | 1.7429 |
| 13.6816 | 0.9811 | 1500 | 1.7293 |
| 13.9706 | 1.0470 | 1600 | 1.7164 |
| 13.6014 | 1.1124 | 1700 | 1.7073 |
| 13.8166 | 1.1778 | 1800 | 1.6967 |
| 14.0799 | 1.2432 | 1900 | 1.6885 |
| 14.2287 | 1.3086 | 2000 | 1.6831 |
| 13.6417 | 1.3740 | 2100 | 1.6771 |
| 14.0925 | 1.4395 | 2200 | 1.6727 |
| 12.2913 | 1.5049 | 2300 | 1.6698 |
| 12.4135 | 1.5703 | 2400 | 1.6679 |
| 13.7286 | 1.6357 | 2500 | 1.6669 |
| 12.4977 | 1.7011 | 2600 | 1.6668 |