End of training
Browse files- README.md +15 -3
- all_results.json +7 -7
- eval_results.json +3 -3
- train_results.json +4 -4
- trainer_state.json +4 -4
README.md
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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:
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- name: lmind_nq_train6000_eval6489_v1_qa_5e-5_lora2
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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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# lmind_nq_train6000_eval6489_v1_qa_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
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It achieves the following results on the evaluation set:
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- Accuracy: 0.5979
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- Loss: 2.3327
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## Model description
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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_nq_train6000_eval6489_v1_qa
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metrics:
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- accuracy
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model-index:
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- name: lmind_nq_train6000_eval6489_v1_qa_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_nq_train6000_eval6489_v1_qa
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type: tyzhu/lmind_nq_train6000_eval6489_v1_qa
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.597948717948718
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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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# lmind_nq_train6000_eval6489_v1_qa_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 the tyzhu/lmind_nq_train6000_eval6489_v1_qa dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3327
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- Accuracy: 0.5979
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## Model description
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all_results.json
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"eval_exact_match": 19.4,
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"eval_f1": 29.764444444444457,
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"eval_loss": 2.33268404006958,
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"eval_runtime": 4.
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"eval_samples": 500,
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"eval_samples_per_second":
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"eval_steps_per_second":
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"perplexity": 10.305564994606339,
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"train_loss": 0.
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"train_runtime":
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"train_samples": 6000,
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"train_samples_per_second":
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"train_steps_per_second":
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}
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"eval_exact_match": 19.4,
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"eval_f1": 29.764444444444457,
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"eval_loss": 2.33268404006958,
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"eval_runtime": 4.6766,
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"eval_samples": 500,
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"eval_samples_per_second": 106.914,
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"eval_steps_per_second": 13.471,
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"perplexity": 10.305564994606339,
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"train_loss": 0.0,
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"train_runtime": 0.143,
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"train_samples": 6000,
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"train_samples_per_second": 2097277.837,
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"train_steps_per_second": 65365.159
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}
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eval_results.json
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"eval_exact_match": 19.4,
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"eval_f1": 29.764444444444457,
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"eval_loss": 2.33268404006958,
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"eval_runtime": 4.
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"eval_samples": 500,
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"eval_samples_per_second":
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"eval_steps_per_second":
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"perplexity": 10.305564994606339
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}
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"eval_exact_match": 19.4,
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"eval_f1": 29.764444444444457,
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"eval_loss": 2.33268404006958,
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"eval_runtime": 4.6766,
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"eval_samples": 500,
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"eval_samples_per_second": 106.914,
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"eval_steps_per_second": 13.471,
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"perplexity": 10.305564994606339
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}
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train_results.json
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{
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"epoch": 49.87,
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"train_loss": 0.
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"train_runtime":
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"train_samples": 6000,
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"train_samples_per_second":
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"train_steps_per_second":
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}
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{
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"epoch": 49.87,
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"train_loss": 0.0,
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"train_runtime": 0.143,
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"train_samples": 6000,
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"train_samples_per_second": 2097277.837,
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"train_steps_per_second": 65365.159
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}
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trainer_state.json
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"epoch": 49.87,
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"step": 9350,
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"total_flos": 3.489165488087368e+17,
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"train_loss": 0.
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second":
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}
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],
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"logging_steps": 100,
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"epoch": 49.87,
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"step": 9350,
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"total_flos": 3.489165488087368e+17,
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"train_loss": 0.0,
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"train_runtime": 0.143,
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"train_samples_per_second": 2097277.837,
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"train_steps_per_second": 65365.159
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}
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],
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"logging_steps": 100,
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