End of training

README.md

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+---
+license: apache-2.0
+base_model: google/bigbird-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: frame_classification_bigbird
+  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. -->
+
+# frame_classification_bigbird
+
+This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8803
+- Accuracy: 0.8991
+- F1: 0.9396
+- Precision: 0.9353
+- Recall: 0.9440
+
+## 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Accuracy | F1     | Validation Loss | Precision | Recall |
+|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:|
+| 0.6673        | 1.0   | 1288  | 0.9270   | 0.9570 | 0.4955          | 0.9390    | 0.9757 |
+| 0.5913        | 2.0   | 2576  | 0.9099   | 0.9477 | 0.6212          | 0.9178    | 0.9795 |
+| 0.5858        | 3.0   | 3864  | 0.9270   | 0.9572 | 0.4327          | 0.9343    | 0.9813 |
+| 0.5384        | 4.0   | 5152  | 0.9317   | 0.9599 | 0.4998          | 0.9377    | 0.9832 |
+| 0.6131        | 5.0   | 6440  | 0.9255   | 0.9561 | 0.5642          | 0.9373    | 0.9757 |
+| 0.5834        | 6.0   | 7728  | 0.9239   | 0.9553 | 0.6238          | 0.9340    | 0.9776 |
+| 0.5023        | 7.0   | 9016  | 0.9208   | 0.9533 | 0.7194          | 0.9354    | 0.9720 |
+| 0.5271        | 8.0   | 10304 | 0.9177   | 0.9516 | 0.7188          | 0.9320    | 0.9720 |
+| 0.4755        | 9.0   | 11592 | 0.8618   | 0.9177 | 0.9514          | 0.9351    | 0.9683 |
+| 0.4173        | 10.0  | 12880 | 0.8803   | 0.8991 | 0.9396          | 0.9353    | 0.9440 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google/bigbird-roberta-base",
+  "architectures": [
+    "BigBirdForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "attention_type": "block_sparse",
+  "block_size": 64,
+  "bos_token_id": 1,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "non-effects",
+    "1": "effects"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "effects": 1,
+    "non-effects": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 4096,
+  "model_type": "big_bird",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "num_random_blocks": 3,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "rescale_embeddings": false,
+  "sep_token_id": 66,
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 2,
+  "use_bias": true,
+  "use_cache": true,
+  "vocab_size": 50358
+}

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special_tokens_map.json

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tokenizer_config.json

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