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Alphatao/f55bf76e-1e88-4ac6-b977-220d58647f04
f55bf76e-1e88-4ac6-b977-220d58647f04 is a machine learning model from Alphatao. 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: teknium/OpenHermes-2.5-Mistral-7B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- dccea3e1ee426787_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/dccea3e1ee426787_train_data.json
type:
field_instruction: inputs
field_output: targets
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
device_map:
? ''
: 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/f55bf76e-1e88-4ac6-b977-220d58647f04
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 966
micro_batch_size: 4
mlflow_experiment_name: /tmp/dccea3e1ee426787_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
special_tokens:
pad_token: <|im_end|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.04514224320834951
wandb_entity: null
wandb_mode: online
wandb_name: 9df2f254-e497-41c8-8189-8a976ae4a8ab
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 9df2f254-e497-41c8-8189-8a976ae4a8ab
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of teknium/OpenHermes-2.5-Mistral-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 |
|---|---|---|---|
| 10.807 | 0.0003 | 1 | 1.3684 |
| 5.7298 | 0.0303 | 100 | 0.6899 |
| 4.6659 | 0.0605 | 200 | 0.6309 |
| 5.1129 | 0.0908 | 300 | 0.6000 |
| 4.4749 | 0.1210 | 400 | 0.5767 |
| 4.5117 | 0.1513 | 500 | 0.5541 |
| 4.1892 | 0.1815 | 600 | 0.5360 |
| 4.1686 | 0.2118 | 700 | 0.5224 |
| 4.0636 | 0.2420 | 800 | 0.5133 |
| 4.0559 | 0.2723 | 900 | 0.5095 |