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CheapsetZero/11de81b5-04ae-4014-9be9-48f46d691f36
11de81b5-04ae-4014-9be9-48f46d691f36 is a machine learning model from CheapsetZero. 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-1.3b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 2bf8960b82477977_train_data.json
ds_type: json
field: prompt
path: /workspace/input_data/
split: train
type: completion
ddp_find_unused_parameters: false
debug: null
deepspeed: null
early_stopping_patience: null
ema_decay: 0.995
ema_update_after_step: 200
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: 1
gradient_checkpointing: true
gradient_clipping: 0.5
greater_is_better: false
group_by_length: false
hub_model_id: CheapsetZero/11de81b5-04ae-4014-9be9-48f46d691f36
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_nan_inf_filter: true
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
lr_scheduler: cosine
max_steps: 14280
metric_for_best_model: eval_loss
micro_batch_size: 16
min_lr: 1.0e-05
mlflow_experiment_name: /tmp/2bf8960b82477977_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
reward_model_sampling_temperature: 0.7
s2_attention: null
sample_packing: false
save_total_limit: 3
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trl:
beta: 0.12
max_completion_length: 768
num_generations: 16
reward_funcs:
- rewards_ce100a7c-0a96-42f4-8866-362f81275652.reward_specific_word_count_normalized
- rewards_ce100a7c-0a96-42f4-8866-362f81275652.reward_short_sentences_normalized
- rewards_ce100a7c-0a96-42f4-8866-362f81275652.reward_low_syllables_per_word_normalized
reward_weights:
- 5.0
- 5.0
- 5.0
use_vllm: false
trust_remote_code: true
use_ema: true
use_peft: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: offline
wandb_name: ce100a7c-0a96-42f4-8866-362f81275652
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: ce100a7c-0a96-42f4-8866-362f81275652
warmup_steps: 714
weight_decay: 0.01
xformers_attention: null
</details><br>
This model is a fine-tuned version of facebook/opt-1.3b 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 |
|---|---|---|---|
| 2.2792 | 0.0002 | 1 | 2.7878 |
| 1.7529 | 0.2076 | 1190 | 1.5526 |
| 1.3549 | 0.4152 | 2380 | 1.4627 |
| 1.4078 | 0.6228 | 3570 | 1.4208 |
| 1.4226 | 0.8304 | 4760 | 1.3871 |
| 1.2185 | 1.0380 | 5950 | 1.3655 |
| 1.435 | 1.2456 | 7140 | 1.3375 |
| 1.1279 | 1.4532 | 8330 | 1.3169 |
| 1.0524 | 1.6609 | 9520 | 1.2995 |
| 1.2777 | 1.8685 | 10710 | 1.2845 |
| 1.1385 | 2.0761 | 11900 | 1.2819 |
| 1.1669 | 2.2837 | 13090 | 1.2779 |
| 1.1292 | 2.4913 | 14280 | 1.2777 |