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-r2a1d0.15-0
+  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-r2a1d0.15-0
+
+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: 0.3672
+- Accuracy: 0.8321
+- Precision: 0.7961
+- Recall: 0.8087
+- F1: 0.8018
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.563         | 1.0   | 122  | 0.5138          | 0.7243   | 0.6636    | 0.6549 | 0.6586 |
+| 0.509         | 2.0   | 244  | 0.5057          | 0.7168   | 0.6763    | 0.6996 | 0.6820 |
+| 0.4924        | 3.0   | 366  | 0.4708          | 0.7393   | 0.6877    | 0.6931 | 0.6901 |
+| 0.468         | 4.0   | 488  | 0.4379          | 0.7845   | 0.7412    | 0.7200 | 0.7286 |
+| 0.4495        | 5.0   | 610  | 0.4466          | 0.7594   | 0.7233    | 0.7548 | 0.7313 |
+| 0.4334        | 6.0   | 732  | 0.4041          | 0.8271   | 0.7927    | 0.7851 | 0.7887 |
+| 0.415         | 7.0   | 854  | 0.4057          | 0.7995   | 0.7590    | 0.7756 | 0.7660 |
+| 0.3974        | 8.0   | 976  | 0.3852          | 0.8321   | 0.7982    | 0.7937 | 0.7959 |
+| 0.3849        | 9.0   | 1098 | 0.3829          | 0.8246   | 0.7880    | 0.7909 | 0.7894 |
+| 0.3771        | 10.0  | 1220 | 0.3786          | 0.8396   | 0.8065    | 0.8065 | 0.8065 |
+| 0.3633        | 11.0  | 1342 | 0.3843          | 0.8296   | 0.7931    | 0.8069 | 0.7993 |
+| 0.3591        | 12.0  | 1464 | 0.3833          | 0.8296   | 0.7931    | 0.8069 | 0.7993 |
+| 0.354         | 13.0  | 1586 | 0.3705          | 0.8396   | 0.8065    | 0.8065 | 0.8065 |
+| 0.3451        | 14.0  | 1708 | 0.3709          | 0.8371   | 0.8028    | 0.8072 | 0.8049 |
+| 0.3403        | 15.0  | 1830 | 0.3733          | 0.8321   | 0.7960    | 0.8112 | 0.8027 |
+| 0.3282        | 16.0  | 1952 | 0.3715          | 0.8346   | 0.7988    | 0.8155 | 0.8061 |
+| 0.3286        | 17.0  | 2074 | 0.3664          | 0.8321   | 0.7965    | 0.8037 | 0.7999 |
+| 0.3348        | 18.0  | 2196 | 0.3670          | 0.8271   | 0.7904    | 0.8001 | 0.7949 |
+| 0.325         | 19.0  | 2318 | 0.3669          | 0.8321   | 0.7961    | 0.8087 | 0.8018 |
+| 0.3266        | 20.0  | 2440 | 0.3672          | 0.8321   | 0.7961    | 0.8087 | 0.8018 |
+
+
+### 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/May17_15-22-38_indolem-petl-vm/events.out.tfevents.1715959362.indolem-petl-vm.1322585.0

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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": 0.15,
+    "init_weights": "lora",
+    "intermediate_lora": false,
+    "leave_out": [],
+    "output_lora": false,
+    "r": 2,
+    "selfattn_lora": true,
+    "use_gating": false
+  },
+  "config_id": "f3eb9f2af424d303",
+  "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,
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+    "head_type": "classification",
+    "label2id": {
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+    "layers": 2,
+    "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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