README.md

metadata

license: apache-2.0
base_model: Falconsai/text_summarization
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: falcon-summ
    results: []

falcon-summ

This model is a fine-tuned version of Falconsai/text_summarization on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.1784
• Rouge1: 0.1921
• Rouge2: 0.0958
• Rougel: 0.1642
• Rougelsum: 0.1643
• Gen Len: 19.0

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	62	2.6597	0.1336	0.0451	0.1109	0.1109	19.0
No log	2.0	124	2.5126	0.1519	0.0584	0.1258	0.1259	19.0
No log	3.0	186	2.4354	0.1702	0.0705	0.142	0.1422	19.0
No log	4.0	248	2.3855	0.1915	0.0922	0.1616	0.1618	19.0
No log	5.0	310	2.3499	0.1932	0.0939	0.1641	0.1644	19.0
No log	6.0	372	2.3251	0.1951	0.0959	0.1665	0.1667	19.0
No log	7.0	434	2.3035	0.1943	0.0963	0.1655	0.1656	19.0
No log	8.0	496	2.2879	0.1941	0.0953	0.1652	0.1653	19.0
2.6368	9.0	558	2.2695	0.1952	0.0958	0.1665	0.1667	19.0
2.6368	10.0	620	2.2588	0.194	0.0952	0.1651	0.1653	19.0
2.6368	11.0	682	2.2476	0.1954	0.0968	0.1668	0.167	19.0
2.6368	12.0	744	2.2396	0.1944	0.0965	0.1656	0.1657	19.0
2.6368	13.0	806	2.2296	0.1929	0.0963	0.1641	0.1644	19.0
2.6368	14.0	868	2.2242	0.1928	0.0969	0.1639	0.1639	19.0
2.6368	15.0	930	2.2159	0.1935	0.0971	0.164	0.1641	19.0
2.6368	16.0	992	2.2114	0.1924	0.0965	0.164	0.1641	19.0
2.3506	17.0	1054	2.2077	0.1926	0.0973	0.1644	0.1645	19.0
2.3506	18.0	1116	2.2031	0.1933	0.0968	0.1647	0.1648	19.0
2.3506	19.0	1178	2.1971	0.1928	0.0962	0.1643	0.1644	19.0
2.3506	20.0	1240	2.1956	0.1925	0.0956	0.165	0.1651	19.0
2.3506	21.0	1302	2.1903	0.1927	0.0958	0.1644	0.1644	19.0
2.3506	22.0	1364	2.1882	0.1933	0.0972	0.1653	0.1653	19.0
2.3506	23.0	1426	2.1858	0.1921	0.0956	0.1639	0.1641	19.0
2.3506	24.0	1488	2.1842	0.1921	0.0956	0.1642	0.1643	19.0
2.2758	25.0	1550	2.1832	0.1919	0.0958	0.1645	0.1647	19.0
2.2758	26.0	1612	2.1815	0.1922	0.0958	0.1646	0.1647	19.0
2.2758	27.0	1674	2.1795	0.1924	0.0962	0.1646	0.1647	19.0
2.2758	28.0	1736	2.1790	0.1922	0.0961	0.1646	0.1647	19.0
2.2758	29.0	1798	2.1784	0.1925	0.0963	0.1645	0.1646	19.0
2.2758	30.0	1860	2.1784	0.1921	0.0958	0.1642	0.1643	19.0

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2