End of training

README.md

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+---
+base_model: BeenaSamuel/t5_small_multi_news_abstractive_summarizer
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: multinews_cnn_logs2
+  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. -->
+
+# multinews_cnn_logs2
+
+This model is a fine-tuned version of [BeenaSamuel/t5_small_multi_news_abstractive_summarizer](https://huggingface.co/BeenaSamuel/t5_small_multi_news_abstractive_summarizer) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7781
+- Rouge1: 0.5231
+- Rouge2: 0.1974
+- Rougel: 0.4013
+- Gen Len: 311.236
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
+| 1.9591        | 0.28  | 200  | 1.8011          | 0.519  | 0.1944 | 0.3973 | 311.236 |
+| 1.8902        | 0.57  | 400  | 1.7998          | 0.5204 | 0.1946 | 0.3979 | 311.236 |
+| 1.8851        | 0.85  | 600  | 1.7963          | 0.5203 | 0.1949 | 0.3981 | 311.236 |
+| 1.9131        | 1.14  | 800  | 1.7947          | 0.52   | 0.1951 | 0.3985 | 311.236 |
+| 1.929         | 1.42  | 1000 | 1.7919          | 0.5204 | 0.1955 | 0.3986 | 311.236 |
+| 1.9045        | 1.71  | 1200 | 1.7881          | 0.5216 | 0.1957 | 0.3995 | 311.236 |
+| 1.9542        | 1.99  | 1400 | 1.7881          | 0.5208 | 0.1959 | 0.3996 | 311.236 |
+| 1.9129        | 2.28  | 1600 | 1.7842          | 0.5218 | 0.1965 | 0.4002 | 311.236 |
+| 1.8727        | 2.56  | 1800 | 1.7848          | 0.5218 | 0.1965 | 0.4001 | 311.236 |
+| 1.9194        | 2.85  | 2000 | 1.7833          | 0.5225 | 0.1968 | 0.4005 | 311.236 |
+| 1.8275        | 3.13  | 2200 | 1.7821          | 0.5223 | 0.1968 | 0.4004 | 311.236 |
+| 1.9338        | 3.42  | 2400 | 1.7809          | 0.5228 | 0.1971 | 0.4007 | 311.236 |
+| 1.9234        | 3.7   | 2600 | 1.7809          | 0.5224 | 0.197  | 0.4008 | 311.236 |
+| 1.904         | 3.98  | 2800 | 1.7795          | 0.5227 | 0.1972 | 0.4009 | 311.236 |
+| 1.8844        | 4.27  | 3000 | 1.7791          | 0.5228 | 0.1973 | 0.4008 | 311.236 |
+| 1.9315        | 4.55  | 3200 | 1.7788          | 0.5228 | 0.1972 | 0.4011 | 311.236 |
+| 1.88          | 4.84  | 3400 | 1.7781          | 0.5231 | 0.1974 | 0.4013 | 311.236 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "BeenaSamuel/t5_small_multi_news_abstractive_summarizer",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 512,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "relu",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": false,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 6,
+  "num_heads": 8,
+  "num_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
+    "summarization": {
+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4,
+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "vocab_size": 32128
+}

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generation_config.json

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+  "_from_model_config": true,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.39.3"
+}

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training_args.bin

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