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--- |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: NousResearch/Llama-2-13b-hf |
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model-index: |
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- name: NobodyExistsOnTheInternet/ToxicQAtextFiltered |
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results: [] |
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--- |
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# Disclaimer: Toxic Content |
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This LoRA is based on a toxic dataset, and its responses when merged to a model may include content that is shocking or disturbing. It is essential to exercise caution and use the LoRA moderately, considering that the generated content is algorithmically derived from the training data. This LoRA is intended for uncensoring purposes only, and users assume responsibility for the interpretation and application of its outputs. I explicitly disclaim endorsement of any specific viewpoints represented in the training data. Additionally, it is crucial to note that the LoRA should not be used for any illegal activities. Users are hereby informed that I am not responsible for any misuse or negative consequences arising from the LoRA's use. Usage of this LoRA implies agreement with these terms. |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.3.0` |
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```yaml |
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base_model: NousResearch/Llama-2-13b-hf |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_llama_derived_model: true |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: dataset |
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type: sharegpt |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./lora-out |
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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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adapter: lora |
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lora_model_dir: |
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lora_r: 128 |
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lora_alpha: 64 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: toxicLlama-2-13B |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 2 |
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num_epochs: 2 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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eval_batch_size: 2 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_table_max_new_tokens: 128 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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# NobodyExistsOnTheInternet/ToxicQAtextFiltered |
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This model is a fine-tuned version of [NousResearch/Llama-2-13b-hf](https://huggingface.co/NousResearch/Llama-2-13b-hf) on the [NobodyExistsOnTheInternet/ToxicQAtextFiltered](https://huggingface.co/datasets/NobodyExistsOnTheInternet/ToxicQAtextFiltered) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7634 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.0107 | 0.0 | 1 | 1.0286 | |
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| 0.8198 | 0.25 | 152 | 0.8079 | |
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| 0.7993 | 0.5 | 304 | 0.7904 | |
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| 0.7348 | 0.75 | 456 | 0.7748 | |
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| 0.689 | 1.0 | 608 | 0.7638 | |
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| 0.6462 | 1.23 | 760 | 0.7729 | |
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| 0.6226 | 1.48 | 912 | 0.7657 | |
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| 0.6179 | 1.73 | 1064 | 0.7634 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: True |
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- load_in_4bit: False |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: fp4 |
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- bnb_4bit_use_double_quant: False |
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- bnb_4bit_compute_dtype: float32 |
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### Framework versions |
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- PEFT 0.6.0 |
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