add model

.gitignore

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+checkpoint-*/

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- scim
+metrics:
+- accuracy
+model_index:
+- name: roberta-base-finetuned-sst2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: scim
+      type: scim
+      args: eod
+    metric:
+      name: Accuracy
+      type: accuracy
+      value: 0.9111111111111111
+---
+
+<!-- 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. -->
+
+# roberta-base-finetuned-sst2
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the scim dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4632
+- Accuracy: 0.9111
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 90   | 2.0273          | 0.6667   |
+| No log        | 2.0   | 180  | 0.8802          | 0.8556   |
+| No log        | 3.0   | 270  | 0.5908          | 0.8889   |
+| No log        | 4.0   | 360  | 0.4632          | 0.9111   |
+| No log        | 5.0   | 450  | 0.4294          | 0.9111   |
+
+
+### Framework versions
+
+- Transformers 4.9.1
+- Pytorch 1.9.0+cu102
+- Datasets 1.11.0
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "roberta-base",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "breach of obligations",
+    "1": "invalidity",
+    "10": "insolvency",
+    "11": "event or events",
+    "12": "repudiation",
+    "13": "judgement",
+    "14": "nationalisation",
+    "15": "others",
+    "16": "legal proceedings",
+    "17": "analogous event",
+    "18": "assets",
+    "19": "jeopardy",
+    "2": "appointment of receiver",
+    "20": "creditor control",
+    "21": "disposal",
+    "3": "composition and arrangement",
+    "4": "non payment",
+    "5": "revocation of license",
+    "6": "cessation of business",
+    "7": "cross default",
+    "8": "winding up",
+    "9": "misrepresentation"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "analogous event": "17",
+    "appointment of receiver": "2",
+    "assets": "18",
+    "breach of obligations": "0",
+    "cessation of business": "6",
+    "composition and arrangement": "3",
+    "creditor control": "20",
+    "cross default": "7",
+    "disposal": "21",
+    "event or events": "11",
+    "insolvency": "10",
+    "invalidity": "1",
+    "jeopardy": "19",
+    "judgement": "13",
+    "legal proceedings": "16",
+    "misrepresentation": "9",
+    "nationalisation": "14",
+    "non payment": "4",
+    "others": "15",
+    "repudiation": "12",
+    "revocation of license": "5",
+    "winding up": "8"
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.9.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

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special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}}

tokenizer_config.json

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+{"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": false, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "roberta-base", "tokenizer_class": "RobertaTokenizer"}

training_args.bin

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