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eddysang/acda19b0-93b9-497b-b53f-6b367306552e
acda19b0-93b9-497b-b53f-6b367306552e is a machine learning model from eddysang. 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. --
Downloads · 30 days
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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: unsloth/llama-2-7b
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 223fc1812f5c799a_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/223fc1812f5c799a_train_data.json
type:
field_instruction: sentence1
field_output: sentence2
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: eddysang/acda19b0-93b9-497b-b53f-6b367306552e
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
lr_scheduler: cosine
max_grad_norm: 2
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/223fc1812f5c799a_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: yaudayah0
wandb_mode: online
wandb_name: 3f50b895-9822-4374-931a-18f0ee2adc53
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 3f50b895-9822-4374-931a-18f0ee2adc53
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false
</details><br>
This model is a fine-tuned version of unsloth/llama-2-7b 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 | nan |
| 0.0 | 0.0068 | 9 | nan |
| 0.0 | 0.0137 | 18 | nan |
| 0.0 | 0.0205 | 27 | nan |
| 0.0 | 0.0273 | 36 | nan |
| 0.0 | 0.0342 | 45 | nan |
| 0.0 | 0.0410 | 54 | nan |
| 0.0 | 0.0479 | 63 | nan |
| 0.0 | 0.0547 | 72 | nan |
| 0.0 | 0.0615 | 81 | nan |
| 0.0 | 0.0684 | 90 | nan |
| 0.0 | 0.0752 | 99 | nan |