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arcwarden46/1386dc5a-0611-4898-8d89-4ce809046786
1386dc5a-0611-4898-8d89-4ce809046786 is a machine learning model from arcwarden46. 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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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/codellama-7b
bf16: true
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 74a276388f1c1ce7_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/74a276388f1c1ce7_train_data.json
type:
field_input: documents
field_instruction: question
field_output: answer
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 3
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: 500
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: false
group_by_length: true
hub_model_id: arcwarden46/1386dc5a-0611-4898-8d89-4ce809046786
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: 10
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 5000
micro_batch_size: 4
mlflow_experiment_name: /tmp/74a276388f1c1ce7_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
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
sequence_len: 1024
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: online
wandb_name: 917bb6eb-c96b-4b8c-8069-b504d0d704c3
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 917bb6eb-c96b-4b8c-8069-b504d0d704c3
warmup_steps: 100
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of unsloth/codellama-7b 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 | 0.0008 | 1 | 1.9227 |
| 0.9445 | 0.4185 | 500 | 1.2826 |
| 0.8743 | 0.8371 | 1000 | 1.2039 |
| 0.8852 | 1.2557 | 1500 | 1.1962 |
| 0.8288 | 1.6743 | 2000 | 1.1846 |
| 0.8665 | 2.0929 | 2500 | 1.1654 |
| 0.8396 | 2.5115 | 3000 | 1.2002 |
| 0.8187 | 2.9300 | 3500 | 1.2045 |
| 0.481 | 3.3486 | 4000 | 1.3219 |