Delete sentiment_classification

sentiment_classification/README.md

@@ -1,70 +0,0 @@
----
-tags:
-- generated_from_trainer
-datasets:
-- financial_phrasebank
-metrics:
-- accuracy
-model-index:
-- name: sentiment_classification
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: financial_phrasebank
-      type: financial_phrasebank
-      config: sentences_66agree
-      split: train
-      args: sentences_66agree
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9265402843601895
----
-
-<!-- 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. -->
-
-# sentiment_classification
-
-This model is a fine-tuned version of [SALT-NLP/FLANG-Roberta](https://huggingface.co/SALT-NLP/FLANG-Roberta) on the financial_phrasebank dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4541
-- Accuracy: 0.9265
-
-## 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: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 6
-
-### Training results
-
-
-
-### Framework versions
-
-- Transformers 4.24.0
-- Pytorch 1.12.1+cu113
-- Datasets 2.7.1
-- Tokenizers 0.13.2

sentiment_classification/config.json

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-{
-  "_name_or_path": "SALT-NLP/FLANG-Roberta",
-  "architectures": [
-    "RobertaForSequenceClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "bos_token_id": 0,
-  "classifier_dropout": null,
-  "eos_token_id": 2,
-  "gradient_checkpointing": false,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2
-  },
-  "layer_norm_eps": 1e-05,
-  "max_position_embeddings": 130,
-  "model_type": "roberta",
-  "num_attention_heads": 12,
-  "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": "4.24.0",
-  "type_vocab_size": 1,
-  "use_cache": true,
-  "vocab_size": 64001
-}

sentiment_classification/pytorch_model.bin

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sentiment_classification/training_args.bin

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