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fats-fme/c8d2f8b9-14c4-4b16-ae1d-d716a2a6e4dc
c8d2f8b9-14c4-4b16-ae1d-d716a2a6e4dc is a machine learning model from fats-fme. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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.safetensors480 MB · 56%
From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: princeton-nlp/Sheared-LLaMA-1.3B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 25dd0e0b52267afa_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/25dd0e0b52267afa_train_data.json
type:
field_input: function_description_en
field_instruction: system_message_en
field_output: system_message_vi
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: fats-fme/c8d2f8b9-14c4-4b16-ae1d-d716a2a6e4dc
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_memory:
0: 130GB
max_steps: 200
micro_batch_size: 2
mlflow_experiment_name: /tmp/25dd0e0b52267afa_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
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
saves_per_epoch: null
sequence_len: 2048
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: 776caaf0-ecf3-4ed0-b0f0-1e847cb24ae0
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 776caaf0-ecf3-4ed0-b0f0-1e847cb24ae0
warmup_steps: 200
weight_decay: 0.01
xformers_attention: null
</details><br>
This model is a fine-tuned version of princeton-nlp/Sheared-LLaMA-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 |
|---|---|---|---|
| No log | 0.0001 | 1 | nan |
| 0.0 | 0.0075 | 100 | nan |
| 0.0 | 0.0150 | 200 | nan |