Update model card.

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distilbert-tweet_eval-emotion
+  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. -->
+
+# distilbert-tweet_eval-emotion
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2519
+- Accuracy: 0.9212
+- Precision: 0.9333
+- Recall: 0.7424
+- F1: 0.8138
+- Auroc: 0.9510
+
+## 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: 1e-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
+- training_steps: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auroc  |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| 0.4845        | 2.5   | 250  | 0.4243          | 0.8061   | 0.2000    | 0.0500 | 0.0800 | 0.9209 |
+| 0.2692        | 5.0   | 500  | 0.2946          | 0.9151   | 0.9333    | 0.7091 | 0.7871 | 0.9469 |
+| 0.192         | 7.5   | 750  | 0.2599          | 0.9151   | 0.9333    | 0.7091 | 0.7871 | 0.9500 |
+| 0.1502        | 10.0  | 1000 | 0.2519          | 0.9212   | 0.9333    | 0.7424 | 0.8138 | 0.9510 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.2
+- Datasets 2.17.0
+- Tokenizers 0.15.1

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "violence",
+    "1": "gender",
+    "2": "race",
+    "3": "sexual_orientation",
+    "4": "religion"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "gender": 1,
+    "race": 2,
+    "religion": 4,
+    "sexual_orientation": 3,
+    "violence": 0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "multi_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "vocab_size": 30522
+}

export/onnx/config.json

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+{
+  "_name_or_path": "outputs/text/multilabel-classification/checkpoint-1000/config.json",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "violence",
+    "1": "gender",
+    "2": "race",
+    "3": "sexual_orientation",
+    "4": "religion"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "gender": 1,
+    "race": 2,
+    "religion": 4,
+    "sexual_orientation": 3,
+    "violence": 0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "multi_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "vocab_size": 30522
+}

export/onnx/model.onnx

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export/onnx/special_tokens_map.json

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export/onnx/tokenizer_config.json

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+}

export/torchscript/model.pt

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export/torchscript/special_tokens_map.json

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export/torchscript/tokenizer_config.json

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+}

model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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+}

training_args.bin

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