add model

README.md

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+---
+metrics:
+- rouge
+
+model-index:
+- name: gq-indo-k
+---
+
+<!-- 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. -->
+
+# gq-indo-k
+
+This model was trained from scratch on an unkown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.7905
+- Rouge1: 22.5734
+- Rouge2: 6.555
+- Rougel: 20.9491
+- Rougelsum: 20.9509
+- Gen Len: 12.0767
+
+## 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: 10
+- eval_batch_size: 10
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 2.9355        | 1.0   | 13032 | 2.8563          | 22.4828 | 6.5456 | 20.8782 | 20.8772   | 11.915  |
+| 2.825         | 2.0   | 26064 | 2.7993          | 22.547  | 6.5815 | 20.8937 | 20.8973   | 12.0886 |
+| 2.7631        | 3.0   | 39096 | 2.7905          | 22.5734 | 6.555  | 20.9491 | 20.9509   | 12.0767 |
+
+
+### Framework versions
+
+- Transformers 4.6.1
+- Pytorch 1.7.0
+- Datasets 1.11.0
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "panggi/t5-small-indonesian-summarization-cased",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 512,
+  "decoder_start_token_id": 0,
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "gradient_checkpointing": false,
+  "initializer_factor": 1.0,
+  "inputs_length": 1024,
+  "is_encoder_decoder": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 1024,
+  "num_decoder_layers": 6,
+  "num_heads": 8,
+  "num_layers": 6,
+  "pad_token_id": 0,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
+    "summarization": {
+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 100,
+      "min_length": 50,
+      "no_repeat_ngram_size": 2,
+      "num_beams": 2,
+      "prefix": "summarize: ",
+      "repetition_penalty": 2.5
+    }
+  },
+  "transformers_version": "4.6.1",
+  "use_cache": true,
+  "vocab_size": 32128
+}

pytorch_model.bin

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