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komodo-ner

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Files changed (30) hide show
  1. README.md +80 -71
  2. adapter_config.json +20 -31
  3. adapter_model.safetensors +2 -2
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  27. special_tokens_map.json +24 -30
  28. tokenizer.json +0 -0
  29. tokenizer_config.json +0 -0
  30. training_args.bin +2 -2
README.md CHANGED
@@ -1,71 +1,80 @@
1
- ---
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- base_model: NousResearch/Llama-2-7b-hf
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- datasets:
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- - conll2003
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- library_name: peft
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- metrics:
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- - precision
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- - recall
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- - f1
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- - accuracy
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- tags:
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- - generated_from_trainer
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- model-index:
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- - name: result
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- results: []
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- ---
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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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-
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- # result
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-
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- This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the conll2003 dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: nan
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- - Precision: 0.0
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- - Recall: 0.0
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- - F1: 0.0
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- - Accuracy: 0.8274
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-
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- ## Model description
32
-
33
- More information needed
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-
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- ## Intended uses & limitations
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-
37
- 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: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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: linear
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- - num_epochs: 3
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
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- | 0.0 | 1.0 | 1756 | nan | 0.0 | 0.0 | 0.0 | 0.8339 |
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- | 0.0 | 2.0 | 3512 | nan | 0.0 | 0.0 | 0.0 | 0.8339 |
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- | 0.0 | 3.0 | 5268 | nan | 0.0 | 0.0 | 0.0 | 0.8339 |
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-
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-
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- ### Framework versions
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-
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- - PEFT 0.12.0
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- - Transformers 4.42.4
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- - Pytorch 2.3.1+cu121
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- - Datasets 2.20.0
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- - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: peft
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+ license: llama2
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+ base_model: Yellow-AI-NLP/komodo-7b-base
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ datasets:
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+ - id_nergrit_corpus
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+ model-index:
12
+ - name: result
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+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
+ should probably proofread and complete it, then remove this comment. -->
18
+
19
+ # result
20
+
21
+ This model is a fine-tuned version of [Yellow-AI-NLP/komodo-7b-base](https://huggingface.co/Yellow-AI-NLP/komodo-7b-base) on the id_nergrit_corpus dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 0.0598
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+ - eval_runtime: 429.4851
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+ - eval_samples_per_second: 1.469
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+ - eval_steps_per_second: 0.368
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+ - epoch: 0.8265
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+ - step: 162
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+
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+ ## Model description
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+
32
+ More information needed
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+
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+ ## Intended uses & limitations
35
+
36
+ More information needed
37
+
38
+ ## Training and evaluation data
39
+
40
+ More information needed
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+
42
+ ## Training procedure
43
+
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+
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+ The following `bitsandbytes` quantization config was used during training:
46
+ - quant_method: bitsandbytes
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+ - _load_in_8bit: False
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+ - _load_in_4bit: True
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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: nf4
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+ - bnb_4bit_use_double_quant: True
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+ - bnb_4bit_compute_dtype: float16
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+ - bnb_4bit_quant_storage: uint8
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+ - load_in_4bit: True
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+ - load_in_8bit: False
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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: 0.0001
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+ - train_batch_size: 4
64
+ - eval_batch_size: 4
65
+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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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_ratio: 0.05
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+ - num_epochs: 2
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+ - mixed_precision_training: Native AMP
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+
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+ ### Framework versions
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+
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+ - PEFT 0.4.0
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+ - Transformers 4.44.1
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+ - Pytorch 2.4.0+cu118
79
+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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