Fine tuning BERT large for InfoVQA

.gitignore

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+checkpoint-*/

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+model-index:
+- name: bert-large-uncased-finetuned-infovqa
+  results:
+  - task:
+      name: Question Answering
+      type: question-answering
+---
+
+<!-- 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. -->
+
+# bert-large-uncased-finetuned-infovqa
+
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 6.3170
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 250500
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 3.7861        | 0.12  | 1000  | 3.2778          |
+| 3.2186        | 0.23  | 2000  | 3.0658          |
+| 2.8504        | 0.35  | 3000  | 3.0456          |
+| 2.8621        | 0.46  | 4000  | 2.8758          |
+| 2.7851        | 0.58  | 5000  | 2.8680          |
+| 2.8016        | 0.69  | 6000  | 2.9244          |
+| 2.7592        | 0.81  | 7000  | 2.7735          |
+| 2.5737        | 0.93  | 8000  | 2.7640          |
+| 2.3493        | 1.04  | 9000  | 2.7257          |
+| 2.1041        | 1.16  | 10000 | 2.8442          |
+| 2.1713        | 1.27  | 11000 | 2.7723          |
+| 2.0594        | 1.39  | 12000 | 2.9982          |
+| 2.1825        | 1.5   | 13000 | 2.8272          |
+| 2.2486        | 1.62  | 14000 | 2.8897          |
+| 2.097         | 1.74  | 15000 | 2.8557          |
+| 2.1645        | 1.85  | 16000 | 2.6342          |
+| 2.15          | 1.97  | 17000 | 2.8680          |
+| 1.5662        | 2.08  | 18000 | 3.2126          |
+| 1.6168        | 2.2   | 19000 | 3.1646          |
+| 1.5886        | 2.32  | 20000 | 3.3139          |
+| 1.6539        | 2.43  | 21000 | 3.2610          |
+| 1.6486        | 2.55  | 22000 | 3.3144          |
+| 1.637         | 2.66  | 23000 | 3.0437          |
+| 1.7186        | 2.78  | 24000 | 2.9936          |
+| 1.7543        | 2.89  | 25000 | 3.1641          |
+| 1.5301        | 3.01  | 26000 | 4.0560          |
+| 1.1436        | 3.13  | 27000 | 4.0116          |
+| 1.1902        | 3.24  | 28000 | 4.0240          |
+| 1.2728        | 3.36  | 29000 | 4.3068          |
+| 1.2586        | 3.47  | 30000 | 3.7894          |
+| 1.3164        | 3.59  | 31000 | 3.9242          |
+| 1.3093        | 3.7   | 32000 | 4.0444          |
+| 1.2812        | 3.82  | 33000 | 4.1779          |
+| 1.3165        | 3.94  | 34000 | 3.6633          |
+| 0.8357        | 4.05  | 35000 | 5.8137          |
+| 0.9583        | 4.17  | 36000 | 5.3305          |
+| 0.9135        | 4.28  | 37000 | 5.4973          |
+| 1.0011        | 4.4   | 38000 | 5.0349          |
+| 0.9553        | 4.51  | 39000 | 5.2086          |
+| 1.0182        | 4.63  | 40000 | 5.1197          |
+| 0.9569        | 4.75  | 41000 | 5.4579          |
+| 0.9437        | 4.86  | 42000 | 5.4467          |
+| 0.9791        | 4.98  | 43000 | 4.7657          |
+| 0.648         | 5.09  | 44000 | 6.5780          |
+| 0.7528        | 5.21  | 45000 | 6.2827          |
+| 0.7247        | 5.33  | 46000 | 6.8500          |
+| 0.702         | 5.44  | 47000 | 6.4572          |
+| 0.6786        | 5.56  | 48000 | 6.5462          |
+| 0.7272        | 5.67  | 49000 | 6.2406          |
+| 0.6778        | 5.79  | 50000 | 6.4727          |
+| 0.6446        | 5.9   | 51000 | 6.3170          |
+
+
+### Framework versions
+
+- Transformers 4.10.0
+- Pytorch 1.8.0+cu101
+- Datasets 1.11.0
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "bert-large-uncased",
+  "architectures": [
+    "BertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.10.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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special_tokens_map.json

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tokenizer_config.json

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