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End of training

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Files changed (6) hide show
  1. README.md +14 -2
  2. all_results.json +15 -0
  3. eval_results.json +10 -0
  4. tokenizer.json +1 -6
  5. train_results.json +8 -0
  6. trainer_state.json +1210 -0
README.md CHANGED
@@ -3,11 +3,23 @@ license: llama2
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  base_model: meta-llama/Llama-2-7b-hf
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
9
  - name: lmind_hotpot_train8000_eval7405_v1_docidx_meta-llama_Llama-2-7b-hf_5e-5_lora2
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- results: []
 
 
 
 
 
 
 
 
 
 
11
  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,7 +27,7 @@ should probably proofread and complete it, then remove this comment. -->
15
 
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  # lmind_hotpot_train8000_eval7405_v1_docidx_meta-llama_Llama-2-7b-hf_5e-5_lora2
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- This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.7747
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  - Accuracy: 0.7938
 
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  base_model: meta-llama/Llama-2-7b-hf
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx
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  metrics:
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  - accuracy
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  model-index:
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  - name: lmind_hotpot_train8000_eval7405_v1_docidx_meta-llama_Llama-2-7b-hf_5e-5_lora2
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+ results:
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+ - task:
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+ name: Causal Language Modeling
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+ type: text-generation
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+ dataset:
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+ name: tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx
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+ type: tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7937900552486188
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  ---
24
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
27
 
28
  # lmind_hotpot_train8000_eval7405_v1_docidx_meta-llama_Llama-2-7b-hf_5e-5_lora2
29
 
30
+ This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.7747
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  - Accuracy: 0.7938
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