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diwank/cryptgpt-large
cryptgpt-large is a text generation model from diwank. Use it when you need the model to write or continue text. It is set up for transformers.
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
# See:
# - https://github.com/karpathy/nanoGPT/blob/master/config/train_gpt2.py#L1
# - https://github.com/OpenAccess-AI-Collective/axolotl/blob/main/examples/tiny-llama/pretrain.yml#L14
# - https://github.com/karpathy/nanoGPT/blob/master/train.py#L35
base_model: diwank/cryptgpt-large
hub_model_id: diwank/cryptgpt-large
model_type: GPT2LMHeadModel
tokenizer_type: AutoTokenizer
trust_remote_code: true # required for CryptGPTTokenizer
resize_token_embeddings_to_32x: true
output_dir: ./outputs/model-out
datasets:
- path: diwank/encrypted-openwebtext
type: completion
dataset_prepared_path: ./cryptgpt-prepared-dataset
val_set_size: 0.04
shuffle_merged_datasets: false
sequence_len: 1024
pad_to_sequence_len: true
sample_packing: false
pretrain_multipack_attn: false
train_on_inputs: true
gradient_accumulation_steps: 1
micro_batch_size: 128
optimizer: adamw_bnb_8bit
adam_beta1: 0.9
adam_beta2: 0.95
seed: 42
lr_scheduler: cosine
learning_rate: 6e-4
cosine_min_lr_ratio: 0.1 # min: 6e-5
weight_decay: 0.15
bf16: auto
tf32: true
flash_attention: true
torch_compile: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
deepspeed: deepspeed_configs/zero2.json
epochs: 20 # overriden by max_steps
max_steps: 600000
eval_steps: 12000
save_steps: 12000
save_total_limit: 3
early_stopping_patience: 3
auto_resume_from_checkpoints: true
logging_steps: 1
eval_max_new_tokens: 128
eval_causal_lm_metrics:
- sacrebleu
wandb_project: cryptgpt-large-0.1
wandb_name: cryptgpt-large-run-04
</details><br>
This model is a fine-tuned version of diwank/cryptgpt-large 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 |
|---|---|---|---|
| 15.7656 | 0.0000 | 1 | 15.4910 |
| 1.8545 | 0.5866 | 12000 | 1.8034 |