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nttx/1ef7560d-80a7-4378-9b0d-2712444de6fe
1ef7560d-80a7-4378-9b0d-2712444de6fe is a machine learning model from nttx. 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 other.
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: facebook/opt-125m
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- d7468c6085d9d274_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/d7468c6085d9d274_train_data.json
type:
field_instruction: instruction
field_output: response
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: 1
gradient_checkpointing: false
group_by_length: true
hub_model_id: nttx/1ef7560d-80a7-4378-9b0d-2712444de6fe
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 3e-5
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 64
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 1500
micro_batch_size: 8
mlflow_experiment_name: /tmp/d7468c6085d9d274_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 15
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: false
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
saves_per_epoch: null
sequence_len: 1024
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: 35a5f6f2-af0f-4744-98c7-ed041dfa95c8
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 35a5f6f2-af0f-4744-98c7-ed041dfa95c8
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null
</details><br>
This model is a fine-tuned version of facebook/opt-125m 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 | 0.0004 | 1 | 3.1619 |
| 2.9044 | 0.0621 | 150 | 2.7964 |
| 2.709 | 0.1241 | 300 | 2.6646 |
| 2.5472 | 0.1862 | 450 | 2.5956 |
| 2.5337 | 0.2482 | 600 | 2.5421 |
| 2.5808 | 0.3103 | 750 | 2.5090 |
| 2.4732 | 0.3724 | 900 | 2.4898 |
| 2.5172 | 0.4344 | 1050 | 2.4748 |
| 2.4349 | 0.4965 | 1200 | 2.4672 |
| 2.425 | 0.5585 | 1350 | 2.4656 |
| 2.4107 | 0.6206 | 1500 | 2.4690 |