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380acb2c-500a-4b09-b01c-c87808f2853a
vmpsergio/380acb2c-500a-4b09-b01c-c87808f2853a
380acb2c-500a-4b09-b01c-c87808f2853a is a machine learning model from vmpsergio. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Model type
- llama
- Access
- Public
- Created
- Apr 30, 2025
- Updated
- Apr 30, 2025
- SHA
- 53b7bd36
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.4.1
absolute_data_files: false
adapter: lora
base_model: NousResearch/Nous-Hermes-llama-2-7b
bf16: true
chat_template: llama3
dataset_prepared_path: /workspace/axolotl
datasets:
- data_files:
- 5cfb94c383f95340_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/5cfb94c383f95340_train_data.json
type:
field_instruction: instruction
field_output: chosen_response
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 1
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 1
gradient_checkpointing: true
gradient_clipping: 0.5
group_by_length: false
hub_model_id: vmpsergio/380acb2c-500a-4b09-b01c-c87808f2853a
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 5.0e-06
load_in_4bit: true
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 200
micro_batch_size: 8
mixed_precision: bf16
mlflow_experiment_name: /tmp/5cfb94c383f95340_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 1
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 10dc235b-06a9-410c-a72b-3ec423544136
wandb_project: s56-2
wandb_run: your_name
wandb_runid: 10dc235b-06a9-410c-a72b-3ec423544136
warmup_steps: 5
weight_decay: 0.01
xformers_attention: true
380acb2c-500a-4b09-b01c-c87808f2853a
This model is a fine-tuned version of NousResearch/Nous-Hermes-llama-2-7b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0100
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9327 | 0.0244 | 200 | 1.0100 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Library
- peft
- Type
- llama
- License
- mit
- Created
- Apr 30, 2025
- Updated
- Apr 30, 2025