End of training

README.md

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+---
+license: mit
+base_model: indobenchmark/indogpt
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bdc2024-indogpt-chatgpt-1
+  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. -->
+
+# bdc2024-indogpt-chatgpt-1
+
+This model is a fine-tuned version of [indobenchmark/indogpt](https://huggingface.co/indobenchmark/indogpt) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4125
+- Accuracy: 0.9120
+- Balanced Accuracy: 0.7419
+- Precision: 0.9074
+- Recall: 0.9120
+- F1: 0.9000
+
+## 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: 16
+- eval_batch_size: 16
+- 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 | Balanced Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 483  | 0.7389          | 0.7859   | 0.5178            | 0.8025    | 0.7859 | 0.7522 |
+| 0.9144        | 2.0   | 966  | 0.5773          | 0.8337   | 0.6070            | 0.8360    | 0.8337 | 0.8036 |
+| 0.5745        | 3.0   | 1449 | 0.4493          | 0.8910   | 0.7056            | 0.8885    | 0.8910 | 0.8747 |
+| 0.3836        | 4.0   | 1932 | 0.4228          | 0.9025   | 0.7261            | 0.8978    | 0.9025 | 0.8878 |
+| 0.2392        | 5.0   | 2415 | 0.4125          | 0.9120   | 0.7419            | 0.9074    | 0.9120 | 0.9000 |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "indobenchmark/indogpt",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2ForSequenceClassification"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7
+  },
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "pad_token_id": 1,
+  "problem_type": "single_label_classification",
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "tokenizer_class": "IndoNLGTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.1",
+  "use_cache": true,
+  "vocab_size": 40005
+}

pytorch_model.bin

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training_args.bin

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