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abaddon182/9e14c1b9-82f4-4963-bbb5-71ae5ec283c2
9e14c1b9-82f4-4963-bbb5-71ae5ec283c2 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 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: Maykeye/TinyLLama-v0
bf16: true
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 77a9490204d171ef_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/77a9490204d171ef_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: abaddon182/9e14c1b9-82f4-4963-bbb5-71ae5ec283c2
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/77a9490204d171ef_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
special_tokens:
pad_token: </s>
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: 6d0bbb9b-bf70-44bf-8e47-c3c296fd19db
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 6d0bbb9b-bf70-44bf-8e47-c3c296fd19db
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null
</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 | 0.0007 | 1 | 11.7835 |
| 8.0876 | 0.1026 | 150 | 8.0951 |
| 7.9559 | 0.2051 | 300 | 7.7923 |
| 7.8329 | 0.3077 | 450 | 7.6951 |
| 7.7323 | 0.4103 | 600 | 7.6072 |
| 7.7037 | 0.5128 | 750 | 7.5229 |
| 7.6448 | 0.6154 | 900 | 7.4841 |
| 7.5287 | 0.7179 | 1050 | 7.4855 |
| 7.6484 | 0.8205 | 1200 | 7.4746 |
| 7.6082 | 0.9231 | 1350 | 7.4811 |
| 7.6381 | 1.0256 | 1500 | 7.4458 |