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tryingpro/2519902a-fb09-443d-927e-50b4e34673ea
2519902a-fb09-443d-927e-50b4e34673ea is a machine learning model from tryingpro. 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.
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/Hermes-3-Llama-3.1-8B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- ac02d0d0203c6ee3_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/ac02d0d0203c6ee3_train_data.json
type:
field_instruction: instruction
field_output: response
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 256
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 32
gradient_checkpointing: true
group_by_length: false
hub_model_id: tryingpro/2519902a-fb09-443d-927e-50b4e34673ea
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: 3
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
- gate_proj
- down_proj
- up_proj
lr_scheduler: cosine
max_grad_norm: 2
max_steps: 90
micro_batch_size: 2
mlflow_experiment_name: /tmp/ac02d0d0203c6ee3_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1.0e-05
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: tryingpro-unicourt
wandb_mode: online
wandb_name: da833b24-e657-43bc-a0c2-8dec63bf1e7f
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: da833b24-e657-43bc-a0c2-8dec63bf1e7f
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false
</details><br>
This model is a fine-tuned version of unsloth/Hermes-3-Llama-3.1-8B 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 | 0.0006 | 1 | nan |
| 0.0 | 0.0051 | 8 | nan |
| 0.0 | 0.0102 | 16 | nan |
| 0.0 | 0.0153 | 24 | nan |
| 0.0 | 0.0204 | 32 | nan |
| 0.0 | 0.0254 | 40 | nan |
| 0.0 | 0.0305 | 48 | nan |
| 0.0 | 0.0356 | 56 | nan |
| 0.0 | 0.0407 | 64 | nan |
| 0.0 | 0.0458 | 72 | nan |
| 0.0 | 0.0509 | 80 | nan |
| 0.0 | 0.0560 | 88 | nan |