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mamung/f7edcc63-fefc-4eae-b622-2e65f127d6b6
f7edcc63-fefc-4eae-b622-2e65f127d6b6 is a machine learning model from mamung. 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: Maykeye/TinyLLama-v0
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 3f7f4544935ed721_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/3f7f4544935ed721_train_data.json
type:
field_input: choices
field_instruction: question
field_output: answer
format: '{instruction} {input}'
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: mamung/f7edcc63-fefc-4eae-b622-2e65f127d6b6
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: 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: 1
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/3f7f4544935ed721_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
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: eddysang
wandb_mode: online
wandb_name: e72b4b00-3aa8-4e69-b8ea-e98f6a2460bf
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e72b4b00-3aa8-4e69-b8ea-e98f6a2460bf
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false
</details><br>
This model is a fine-tuned version of Maykeye/TinyLLama-v0 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 | 0.6275 | 1 | 7.9386 |
| No log | 1.5294 | 2 | 7.9391 |
| 12.4178 | 2.4314 | 3 | 7.9329 |
| 12.4178 | 3.3333 | 4 | 7.9338 |
| 12.4178 | 4.2353 | 5 | 7.9312 |