jorgeduardo13
commited on
Commit
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Lo logramos de nuevo equipo Platzi! 🤗
Browse files- README.md +8 -7
- all_results.json +11 -11
- eval_results.json +7 -7
- train_results.json +5 -5
README.md
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license: apache-2.0
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base_model: distilbert-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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name: Text Classification
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type: text-classification
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dataset:
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name:
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type: glue
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config: mrpc
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split: validation
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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- name: F1
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type: f1
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value: 0.
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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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# platzi-distilbert-model-similaritytexts-JorgeEnciso
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: 0.
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## Model description
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- text-classification
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- generated_from_trainer
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datasets:
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- glue
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name: Text Classification
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type: text-classification
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dataset:
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name: datasetX
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type: glue
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config: mrpc
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split: validation
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7083333333333334
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- name: F1
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type: f1
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value: 0.8125984251968503
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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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# platzi-distilbert-model-similaritytexts-JorgeEnciso
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the datasetX dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5871
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- Accuracy: 0.7083
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- F1: 0.8126
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## Model description
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all_results.json
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{
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"epoch":
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"eval_accuracy": 0.
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"eval_f1": 0.
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"eval_loss": 0.
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"eval_runtime": 2.
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"eval_samples_per_second":
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"eval_steps_per_second":
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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": 16.
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}
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{
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"epoch": 5.0,
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"eval_accuracy": 0.7083333333333334,
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"eval_f1": 0.8125984251968503,
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"eval_loss": 0.5871198773384094,
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"eval_runtime": 2.5693,
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"eval_samples_per_second": 158.801,
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"eval_steps_per_second": 19.85,
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"train_loss": 0.5974179269961023,
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"train_runtime": 138.812,
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"train_samples_per_second": 132.121,
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"train_steps_per_second": 16.533
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}
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eval_results.json
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{
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"epoch":
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"eval_accuracy": 0.
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"eval_f1": 0.
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"eval_loss": 0.
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"eval_runtime": 2.
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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": 5.0,
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"eval_accuracy": 0.7083333333333334,
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"eval_f1": 0.8125984251968503,
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"eval_loss": 0.5871198773384094,
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"eval_runtime": 2.5693,
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"eval_samples_per_second": 158.801,
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"eval_steps_per_second": 19.85
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}
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train_results.json
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{
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"epoch":
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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": 16.
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}
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{
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"epoch": 5.0,
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"train_loss": 0.5974179269961023,
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"train_runtime": 138.812,
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"train_samples_per_second": 132.121,
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"train_steps_per_second": 16.533
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}
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