tejaskamtam
commited on
Commit
•
52d9354
1
Parent(s):
59081f4
End of training
Browse files- README.md +16 -5
- all_results.json +15 -0
- eval_results.json +10 -0
- train_results.json +8 -0
- trainer_state.json +780 -0
README.md
CHANGED
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---
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-
license: apache-2.0
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base_model: facebook/bart-base
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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: bart-base-finetuned-xe_ey_fae
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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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@@ -15,10 +26,10 @@ should probably proofread and complete it, then remove this comment. -->
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# bart-base-finetuned-xe_ey_fae
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on
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It achieves the following results on the evaluation set:
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- Loss: 1.
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-
- Accuracy: 0.
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## Model description
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---
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base_model: facebook/bart-base
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tags:
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- generated_from_trainer
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+
datasets:
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+
- datasets/all_binary_and_xe_ey_fae_counterfactual
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metrics:
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- accuracy
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model-index:
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- name: bart-base-finetuned-xe_ey_fae
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results:
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- task:
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name: Masked Language Modeling
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type: fill-mask
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dataset:
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name: datasets/all_binary_and_xe_ey_fae_counterfactual
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type: datasets/all_binary_and_xe_ey_fae_counterfactual
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7180178883360112
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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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# bart-base-finetuned-xe_ey_fae
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+
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the datasets/all_binary_and_xe_ey_fae_counterfactual dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3945
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- Accuracy: 0.7180
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## Model description
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all_results.json
ADDED
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{
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"epoch": 3.0,
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"eval_accuracy": 0.7180178883360112,
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"eval_loss": 1.3944889307022095,
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"eval_runtime": 95.1252,
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"eval_samples": 16928,
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"eval_samples_per_second": 177.955,
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"eval_steps_per_second": 22.244,
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"perplexity": 4.032912947872197,
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"train_loss": 2.057705193860182,
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"train_runtime": 15314.6638,
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"train_samples": 135339,
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"train_samples_per_second": 26.512,
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"train_steps_per_second": 1.657
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}
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eval_results.json
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{
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"epoch": 3.0,
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"eval_accuracy": 0.7180178883360112,
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"eval_loss": 1.3944889307022095,
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"eval_runtime": 95.1252,
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"eval_samples": 16928,
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"eval_samples_per_second": 177.955,
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"eval_steps_per_second": 22.244,
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"perplexity": 4.032912947872197
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}
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train_results.json
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{
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"epoch": 3.0,
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"train_loss": 2.057705193860182,
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"train_runtime": 15314.6638,
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"train_samples": 135339,
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"train_samples_per_second": 26.512,
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"train_steps_per_second": 1.657
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}
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trainer_state.json
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+
{
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"best_metric": 1.3909834623336792,
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"best_model_checkpoint": "finetuning/output/bart-base-finetuned_xe_ey_fae/checkpoint-25000",
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"epoch": 3.0,
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"eval_steps": 500,
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"global_step": 25377,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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"step": 500
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{
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"epoch": 0.06,
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"eval_accuracy": 0.3627901941481408,
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"eval_runtime": 98.6024,
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"eval_samples_per_second": 171.679,
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"eval_steps_per_second": 21.46,
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"step": 500
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},
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{
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"epoch": 0.12,
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"learning_rate": 9.607518619222132e-06,
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"loss": 4.0408,
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"step": 1000
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},
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{
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"epoch": 0.12,
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"eval_accuracy": 0.46300121473546585,
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"eval_loss": 3.057621717453003,
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"eval_runtime": 99.414,
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"eval_samples_per_second": 170.278,
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"eval_steps_per_second": 21.285,
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"step": 1000
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},
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{
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"epoch": 0.18,
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"learning_rate": 9.41048981361075e-06,
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"loss": 3.4979,
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"step": 1500
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},
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{
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"epoch": 0.18,
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"eval_accuracy": 0.5132904448434071,
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"eval_loss": 2.70158314704895,
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"eval_runtime": 99.9098,
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"eval_samples_per_second": 169.433,
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"eval_steps_per_second": 21.179,
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"step": 1500
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},
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{
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"epoch": 0.24,
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"learning_rate": 9.21346100799937e-06,
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"loss": 3.1691,
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"step": 2000
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