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Browse files- README.md +142 -0
- adapter_config.json +34 -0
- adapter_model.bin +3 -0
- checkpoint-1569/README.md +202 -0
- checkpoint-1569/adapter_config.json +34 -0
- checkpoint-1569/adapter_model.safetensors +3 -0
- checkpoint-1569/optimizer.pt +3 -0
- checkpoint-1569/rng_state.pth +3 -0
- checkpoint-1569/scheduler.pt +3 -0
- checkpoint-1569/special_tokens_map.json +24 -0
- checkpoint-1569/tokenizer.model +3 -0
- checkpoint-1569/tokenizer_config.json +43 -0
- checkpoint-1569/trainer_state.json +0 -0
- checkpoint-1569/training_args.bin +3 -0
- config.json +45 -0
- merged/config.json +30 -0
- merged/generation_config.json +8 -0
- merged/pytorch_model-00001-of-00002.bin +3 -0
- merged/pytorch_model-00002-of-00002.bin +3 -0
- merged/pytorch_model.bin.index.json +244 -0
- merged/special_tokens_map.json +24 -0
- merged/tokenizer.model +3 -0
- merged/tokenizer_config.json +43 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
README.md
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---
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base_model: openlm-research/open_llama_3b_v2
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library_name: peft
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: outputs/lora-out
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results: []
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---
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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: `0.4.1`
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```yaml
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base_model: openlm-research/open_llama_3b_v2
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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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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push_dataset_to_hub:
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datasets:
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- path: Sourabh2/Alphaca_data
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type: alpaca
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dataset_prepared_path:
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val_set_size: 0.02
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adapter: lora
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lora_model_dir:
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sequence_len: 1024
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sample_packing: true
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.0
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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+
- o_proj
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lora_fan_in_fan_out:
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+
wandb_project:
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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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output_dir: ./outputs/lora-out
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gradient_accumulation_steps: 1
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+
micro_batch_size: 2
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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+
torchdistx_path:
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+
lr_scheduler: cosine
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learning_rate: 0.0002
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train_on_inputs: false
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group_by_length: false
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bf16: false
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fp16: true
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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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+
gptq_groupsize:
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+
s2_attention:
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+
gptq_model_v1:
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warmup_steps: 20
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evals_per_epoch: 4
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.1
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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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```
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</details><br>
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# outputs/lora-out
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This model is a fine-tuned version of [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2601
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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+
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## Training and evaluation data
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|
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More information needed
|
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+
|
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## Training procedure
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|
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### Training hyperparameters
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|
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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: 20
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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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|
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.034 | 0.0006 | 1 | 1.0952 |
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| 0.2894 | 0.2505 | 393 | 0.3186 |
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| 0.2138 | 0.5010 | 786 | 0.2808 |
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| 0.2722 | 0.7514 | 1179 | 0.2601 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.41.1
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- Pytorch 2.1.2+cu118
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "openlm-research/open_llama_3b_v2",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.0,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
|
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"revision": null,
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"target_modules": [
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"q_proj",
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"up_proj",
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"k_proj",
|
26 |
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"v_proj",
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27 |
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"gate_proj",
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"down_proj",
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29 |
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"o_proj"
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],
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"task_type": "CAUSAL_LM",
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32 |
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"use_dora": false,
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33 |
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"use_rslora": false
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34 |
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b2eaeabb76da5d7aec66ffbd0a9ebef9986a0320fab0b36a180c3b1f14731a2a
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size 50982842
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checkpoint-1569/README.md
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---
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base_model: openlm-research/open_llama_3b_v2
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library_name: peft
|
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---
|
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+
|
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# Model Card for Model ID
|
7 |
+
|
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+
<!-- Provide a quick summary of what the model is/does. -->
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9 |
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|
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+
|
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|
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## Model Details
|
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|
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### Model Description
|
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|
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<!-- Provide a longer summary of what this model is. -->
|
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|
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|
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|
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- **Developed by:** [More Information Needed]
|
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- **Funded by [optional]:** [More Information Needed]
|
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- **Shared by [optional]:** [More Information Needed]
|
23 |
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- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
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- **License:** [More Information Needed]
|
26 |
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- **Finetuned from model [optional]:** [More Information Needed]
|
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+
|
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### Model Sources [optional]
|
29 |
+
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<!-- Provide the basic links for the model. -->
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|
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- **Repository:** [More Information Needed]
|
33 |
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- **Paper [optional]:** [More Information Needed]
|
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- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
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## Uses
|
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|
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
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|
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### Direct Use
|
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|
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
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|
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[More Information Needed]
|
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|
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### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
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|
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[More Information Needed]
|
51 |
+
|
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### Out-of-Scope Use
|
53 |
+
|
54 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
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|
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[More Information Needed]
|
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+
|
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## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
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[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
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+
|
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+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
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+
|
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## How to Get Started with the Model
|
71 |
+
|
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Use the code below to get started with the model.
|
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+
|
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+
[More Information Needed]
|
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+
|
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## Training Details
|
77 |
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|
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### Training Data
|
79 |
+
|
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+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
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|
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[More Information Needed]
|
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+
|
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### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
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+
|
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#### Preprocessing [optional]
|
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+
|
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[More Information Needed]
|
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+
|
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+
|
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#### Training Hyperparameters
|
94 |
+
|
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
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+
|
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#### Speeds, Sizes, Times [optional]
|
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|
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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|
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[More Information Needed]
|
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|
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## Evaluation
|
104 |
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|
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<!-- This section describes the evaluation protocols and provides the results. -->
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|
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
|
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|
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[More Information Needed]
|
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|
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+
#### Factors
|
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|
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+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
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[More Information Needed]
|
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+
|
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+
#### Metrics
|
122 |
+
|
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+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
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|
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[More Information Needed]
|
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|
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+
### Results
|
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|
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[More Information Needed]
|
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|
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#### Summary
|
132 |
+
|
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+
|
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+
|
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+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
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+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
### Framework versions
|
201 |
+
|
202 |
+
- PEFT 0.11.1
|
checkpoint-1569/adapter_config.json
ADDED
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|
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|
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|
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|
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|
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|
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|
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