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abaddon182/7614ef6a-9f38-4595-a0e5-92e37db02045
7614ef6a-9f38-4595-a0e5-92e37db02045 is a machine learning model from abaddon182. 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 other.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/Qwen2.5-3B
bf16: true
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 0df8fedfbf56abe9_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/0df8fedfbf56abe9_train_data.json
type:
field_instruction: instruction
field_output: output
format: '{instruction}'
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: 8
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: true
hub_model_id: abaddon182/7614ef6a-9f38-4595-a0e5-92e37db02045
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: 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_grad_norm: 1.0
max_steps: 1500
micro_batch_size: 8
mlflow_experiment_name: /tmp/0df8fedfbf56abe9_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-8
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: 150
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: 678aaedc-9d7f-4f3b-bd22-c956652dc5ed
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 678aaedc-9d7f-4f3b-bd22-c956652dc5ed
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null
</details><br>
This model is a fine-tuned version of unsloth/Qwen2.5-3B 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 | 0.0007 | 1 | 0.8236 |
| 0.6707 | 0.1026 | 150 | 0.5631 |
| 0.5641 | 0.2051 | 300 | 0.5423 |
| 0.6515 | 0.3077 | 450 | 0.5308 |
| 0.5612 | 0.4103 | 600 | 0.5255 |
| 0.5696 | 0.5128 | 750 | 0.5140 |
| 0.5035 | 0.6154 | 900 | 0.5074 |
| 0.5933 | 0.7179 | 1050 | 0.5062 |
| 0.474 | 0.8205 | 1200 | 0.4993 |
| 0.46 | 0.9231 | 1350 | 0.4999 |
| 0.3632 | 1.0256 | 1500 | 0.5005 |