asahi417 commited on
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db6d0eb
1 Parent(s): a516a60

model update

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Files changed (2) hide show
  1. README.md +6 -6
  2. metric_summary.json +1 -1
README.md CHANGED
@@ -18,13 +18,13 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.10513880685174248
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  - name: F1 (macro)
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  type: f1_macro
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- value: 0.031712096917869234
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  - name: Accuracy
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  type: accuracy
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- value: 0.10513880685174247
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  pipeline_tag: text-classification
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  widget:
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  - text: "I'm sure the {@Tampa Bay Lightning@} would’ve rather faced the Flyers but man does their experience versus the Blue Jackets this year and last help them a lot versus this Islanders team. Another meat grinder upcoming for the good guys"
@@ -37,9 +37,9 @@ widget:
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [tweet_topic_single](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single). This model is fine-tuned on `train_all` split and validated on `test_2021` split of tweet_topic.
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  Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single/blob/main/lm_finetuning.py). It achieves the following results on the test_2021 set:
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- - F1 (micro): 0.10513880685174248
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- - F1 (macro): 0.031712096917869234
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- - Accuracy: 0.10513880685174247
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  ### Usage
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.8877731836975783
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  - name: F1 (macro)
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  type: f1_macro
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+ value: 0.7979301633555328
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8877731836975783
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  pipeline_tag: text-classification
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  widget:
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  - text: "I'm sure the {@Tampa Bay Lightning@} would’ve rather faced the Flyers but man does their experience versus the Blue Jackets this year and last help them a lot versus this Islanders team. Another meat grinder upcoming for the good guys"
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [tweet_topic_single](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single). This model is fine-tuned on `train_all` split and validated on `test_2021` split of tweet_topic.
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  Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single/blob/main/lm_finetuning.py). It achieves the following results on the test_2021 set:
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+ - F1 (micro): 0.8877731836975783
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+ - F1 (macro): 0.7979301633555328
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+ - Accuracy: 0.8877731836975783
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  ### Usage
metric_summary.json CHANGED
@@ -1 +1 @@
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- {"test/eval_loss": 1.9087095260620117, "test/eval_f1": 0.10513880685174248, "test/eval_f1_macro": 0.031712096917869234, "test/eval_accuracy": 0.10513880685174247, "test/eval_runtime": 49.8317, "test/eval_samples_per_second": 33.974, "test/eval_steps_per_second": 2.127}
 
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+ {"test/eval_loss": 0.5947489142417908, "test/eval_f1": 0.8877731836975783, "test/eval_f1_macro": 0.7979301633555328, "test/eval_accuracy": 0.8877731836975783, "test/eval_runtime": 49.3859, "test/eval_samples_per_second": 34.281, "test/eval_steps_per_second": 2.146}