Model save

README.md

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+---
+license: mit
+base_model: indolem/indobert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: sentiment-lora-r2a1d0.05-1
+  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. -->
+
+# sentiment-lora-r2a1d0.05-1
+
+This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3638
+- Accuracy: 0.8446
+- Precision: 0.8193
+- Recall: 0.7951
+- F1: 0.8055
+
+## 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: 5e-05
+- train_batch_size: 30
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5663        | 1.0   | 122  | 0.5216          | 0.7293   | 0.6677    | 0.6510 | 0.6572 |
+| 0.5149        | 2.0   | 244  | 0.5134          | 0.7243   | 0.6758    | 0.6899 | 0.6810 |
+| 0.4925        | 3.0   | 366  | 0.4821          | 0.7569   | 0.7055    | 0.6980 | 0.7014 |
+| 0.4608        | 4.0   | 488  | 0.4654          | 0.7644   | 0.7150    | 0.7083 | 0.7114 |
+| 0.4493        | 5.0   | 610  | 0.4600          | 0.7569   | 0.7126    | 0.7305 | 0.7193 |
+| 0.4257        | 6.0   | 732  | 0.4307          | 0.7870   | 0.7433    | 0.7318 | 0.7369 |
+| 0.4178        | 7.0   | 854  | 0.4181          | 0.7970   | 0.7552    | 0.7614 | 0.7581 |
+| 0.3977        | 8.0   | 976  | 0.3972          | 0.8070   | 0.7687    | 0.7560 | 0.7617 |
+| 0.3946        | 9.0   | 1098 | 0.3937          | 0.8145   | 0.7779    | 0.7663 | 0.7716 |
+| 0.3762        | 10.0  | 1220 | 0.3874          | 0.8246   | 0.7995    | 0.7584 | 0.7738 |
+| 0.3727        | 11.0  | 1342 | 0.3787          | 0.8321   | 0.8014    | 0.7837 | 0.7915 |
+| 0.3626        | 12.0  | 1464 | 0.3750          | 0.8371   | 0.8059    | 0.7947 | 0.7999 |
+| 0.359         | 13.0  | 1586 | 0.3728          | 0.8296   | 0.8066    | 0.7644 | 0.7803 |
+| 0.3488        | 14.0  | 1708 | 0.3709          | 0.8296   | 0.8049    | 0.7669 | 0.7816 |
+| 0.3445        | 15.0  | 1830 | 0.3667          | 0.8421   | 0.8131    | 0.7983 | 0.8050 |
+| 0.3344        | 16.0  | 1952 | 0.3656          | 0.8421   | 0.8142    | 0.7958 | 0.8040 |
+| 0.3339        | 17.0  | 2074 | 0.3654          | 0.8396   | 0.8128    | 0.7890 | 0.7992 |
+| 0.3357        | 18.0  | 2196 | 0.3638          | 0.8421   | 0.8154    | 0.7933 | 0.8029 |
+| 0.3357        | 19.0  | 2318 | 0.3646          | 0.8421   | 0.8154    | 0.7933 | 0.8029 |
+| 0.3359        | 20.0  | 2440 | 0.3638          | 0.8446   | 0.8193    | 0.7951 | 0.8055 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.15.2

default/head_config.json

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+    "activation_function": "gelu",
+    "bias": true,
+    "embedding_size": 768,
+    "head_type": "masked_lm",
+    "label2id": null,
+    "layer_norm": true,
+    "layers": 2,
+    "shift_labels": false,
+    "vocab_size": 31923
+  },
+  "hidden_size": 768,
+  "model_class": "BertAdapterModel",
+  "model_name": "indolem/indobert-base-uncased",
+  "model_type": "bert",
+  "name": "default",
+  "version": "0.2.0"
+}

default/pytorch_model_head.bin

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runs/May18_19-58-02_indolem-petl-vm/events.out.tfevents.1716062287.indolem-petl-vm.1915283.0

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sentiment-lora/adapter_config.json

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+  "config": {
+    "alpha": 1,
+    "architecture": "lora",
+    "attn_matrices": [
+      "q",
+      "v"
+    ],
+    "composition_mode": "add",
+    "dropout": 0.05,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 2,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "2a03db0209186bb9",
+  "hidden_size": 768,
+  "model_class": "BertAdapterModel",
+  "model_name": "indolem/indobert-base-uncased",
+  "model_type": "bert",
+  "name": "sentiment-lora",
+  "version": "0.2.0"
+}

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sentiment/head_config.json

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+{
+  "config": {
+    "activation_function": "tanh",
+    "bias": true,
+    "dropout_prob": null,
+    "head_type": "classification",
+    "label2id": {
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+      "1": 1
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+    "num_labels": 2,
+    "use_pooler": false
+  },
+  "hidden_size": 768,
+  "model_class": "BertAdapterModel",
+  "model_name": "indolem/indobert-base-uncased",
+  "model_type": "bert",
+  "name": "sentiment",
+  "version": "0.2.0"
+}

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