End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,76 @@
+---
+base_model: csebuetnlp/mT5_multilingual_XLSum
+tags:
+- generated_from_trainer
+model-index:
+- name: type2_neg_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. -->
+
+# type2_neg_1
+
+This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.0065
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 3.7124        | 0.49  | 500   | 3.2054          |
+| 3.3429        | 0.98  | 1000  | 2.9874          |
+| 2.9583        | 1.47  | 1500  | 2.9013          |
+| 3.0351        | 1.96  | 2000  | 2.8271          |
+| 2.5532        | 2.46  | 2500  | 2.8162          |
+| 2.5494        | 2.95  | 3000  | 2.8092          |
+| 2.5826        | 3.44  | 3500  | 2.8252          |
+| 2.0509        | 3.93  | 4000  | 2.8108          |
+| 2.1758        | 4.42  | 4500  | 2.8365          |
+| 1.9913        | 4.91  | 5000  | 2.8331          |
+| 1.5736        | 5.4   | 5500  | 2.9037          |
+| 2.3872        | 5.89  | 6000  | 2.8933          |
+| 1.758         | 6.39  | 6500  | 2.9362          |
+| 1.6921        | 6.88  | 7000  | 2.9323          |
+| 1.7101        | 7.37  | 7500  | 2.9635          |
+| 1.6037        | 7.86  | 8000  | 2.9728          |
+| 1.3991        | 8.35  | 8500  | 3.0027          |
+| 1.5043        | 8.84  | 9000  | 2.9930          |
+| 1.808         | 9.33  | 9500  | 3.0045          |
+| 1.4231        | 9.82  | 10000 | 3.0065          |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

@@ -0,0 +1,37 @@
+{
+  "_name_or_path": "csebuetnlp/mT5_multilingual_XLSum",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "length_penalty": 0.6,
+  "max_length": 84,
+  "model_type": "mt5",
+  "no_repeat_ngram_size": 2,
+  "num_beams": 4,
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 250112
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "length_penalty": 0.6,
+  "max_length": 84,
+  "no_repeat_ngram_size": 2,
+  "num_beams": 4,
+  "pad_token_id": 0,
+  "transformers_version": "4.38.2"
+}

model.safetensors

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runs/Apr10_14-03-52_b94d93c0e033/events.out.tfevents.1712757833.b94d93c0e033.21819.0

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special_tokens_map.json

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spiece.model

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tokenizer.json

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tokenizer_config.json

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+  "added_tokens_decoder": {
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+  "clean_up_tokenization_spaces": true,
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+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "T5Tokenizer",
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+}

training_args.bin

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