End of training
Browse files- README.md +19 -4
- all_results.json +8 -8
- config.json +1 -0
- eval_results.json +5 -5
- train_results.json +3 -3
- trainer_state.json +3 -3
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: bert-base-uncased
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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: bert-base-uncased-finetuned-qnli
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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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# bert-base-uncased-finetuned-qnli
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on
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It achieves the following results on the evaluation set:
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## Model description
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---
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library_name: transformers
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language:
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- en
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license: apache-2.0
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base_model: bert-base-uncased
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: bert-base-uncased-finetuned-qnli
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: GLUE QNLI
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type: glue
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args: qnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9114039904814205
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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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# bert-base-uncased-finetuned-qnli
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QNLI dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4043
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- Accuracy: 0.9114
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## Model description
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all_results.json
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{
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"epoch": 3.0,
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"eval_accuracy": 0.
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"eval_loss": 0.
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"eval_runtime":
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"eval_samples": 5463,
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"eval_samples_per_second":
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"eval_steps_per_second":
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"total_flos": 8.267712381471744e+16,
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"train_loss": 0.0,
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"train_runtime": 0.
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"train_samples": 104743,
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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": 3.0,
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"eval_accuracy": 0.9114039904814205,
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"eval_loss": 0.40430235862731934,
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"eval_runtime": 438.058,
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"eval_samples": 5463,
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"eval_samples_per_second": 12.471,
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"eval_steps_per_second": 1.559,
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"total_flos": 8.267712381471744e+16,
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"train_loss": 0.0,
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"train_runtime": 0.0012,
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"train_samples": 104743,
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"train_samples_per_second": 253407412.347,
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"train_steps_per_second": 15839324.142
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}
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config.json
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.45.0.dev0",
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"type_vocab_size": 2,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.45.0.dev0",
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"type_vocab_size": 2,
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eval_results.json
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{
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"epoch": 3.0,
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"eval_accuracy": 0.
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"eval_loss": 0.
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"eval_runtime":
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"eval_samples": 5463,
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"eval_samples_per_second":
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"eval_steps_per_second":
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}
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{
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"epoch": 3.0,
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"eval_accuracy": 0.9114039904814205,
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"eval_loss": 0.40430235862731934,
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"eval_runtime": 438.058,
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"eval_samples": 5463,
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"eval_samples_per_second": 12.471,
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"eval_steps_per_second": 1.559
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}
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train_results.json
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"epoch": 3.0,
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"total_flos": 8.267712381471744e+16,
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"train_loss": 0.0,
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"train_runtime": 0.
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"train_samples": 104743,
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"train_samples_per_second":
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"train_steps_per_second":
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}
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"epoch": 3.0,
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"total_flos": 8.267712381471744e+16,
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"train_loss": 0.0,
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"train_runtime": 0.0012,
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"train_samples": 104743,
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"train_samples_per_second": 253407412.347,
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"train_steps_per_second": 15839324.142
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}
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trainer_state.json
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"step": 19641,
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"total_flos": 8.267712381471744e+16,
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"train_loss": 0.0,
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"train_runtime": 0.
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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": 500,
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"step": 19641,
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"total_flos": 8.267712381471744e+16,
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"train_loss": 0.0,
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"train_runtime": 0.0012,
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"train_samples_per_second": 253407412.347,
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"train_steps_per_second": 15839324.142
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}
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],
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"logging_steps": 500,
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