klorine28 commited on Apr 7

Commit

bcf17c2

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1 Parent(s): f7fa530

End of training

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README.md CHANGED Viewed

@@ -1,3 +1,62 @@
 ---
-license: cc
 ---

 ---
+base_model: finiteautomata/bertweet-base-sentiment-analysis
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: finetuning-sentiment-model-1000-samples
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# finetuning-sentiment-model-1000-samples
+This model is a fine-tuned version of [finiteautomata/bertweet-base-sentiment-analysis](https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0417
+- Accuracy: 0.9962
+- F1: 0.9965
+- Recall: 0.9977
+- Precision: 0.9953
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+### Training results
+### Framework versions
+- Transformers 4.39.3
+- Pytorch 1.13.1+cpu
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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config.json ADDED Viewed

+{
+  "_name_or_path": "finiteautomata/bertweet-base-sentiment-analysis",
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+    "RobertaForSequenceClassification"
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+  "initializer_range": 0.02,
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+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 130,
+  "model_type": "roberta",
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+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tokenizer_class": "BertweetTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 64001
+}

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