m2m100_418M-lecturaFacil

This model is a fine-tuned version of facebook/m2m100_418M on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0661
• Rouge1: 43.385
• Rouge2: 32.8564
• Rougel: 33.7117
• Rougelsum: 42.0926

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: 5.6e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	126	1.7497	36.685	26.6869	30.2571	35.0041
2.0989	2.0	252	1.3739	40.2068	30.7895	33.2676	38.7904
2.0989	3.0	378	1.2066	43.2475	34.7388	36.3563	41.9648
1.217	4.0	504	1.0995	41.3675	31.9862	34.2429	40.0616
1.217	5.0	630	1.0401	41.7939	31.5659	33.7242	40.4383
0.8874	6.0	756	0.9996	42.1276	33.2102	35.023	40.7052
0.8874	7.0	882	0.9638	42.0925	32.145	34.0498	40.6997
0.6815	8.0	1008	0.9428	43.2718	34.0356	35.7494	41.9982
0.6815	9.0	1134	0.9420	43.4868	34.301	35.5118	42.3057
0.5505	10.0	1260	0.9328	41.9763	32.0642	33.8328	40.6177
0.5505	11.0	1386	0.9290	43.7249	34.629	35.8741	42.4228
0.4493	12.0	1512	0.9381	43.2557	33.8024	35.1489	41.9791
0.4493	13.0	1638	0.9413	41.7681	30.7291	31.8306	40.3795
0.3818	14.0	1764	0.9471	42.3205	31.4222	32.7127	40.8971
0.3818	15.0	1890	0.9592	43.3617	33.3281	34.1906	42.0589
0.3123	16.0	2016	0.9687	42.9163	32.1448	33.1292	41.5772
0.3123	17.0	2142	0.9803	43.6651	33.4911	34.4811	42.3598
0.2588	18.0	2268	0.9851	43.9449	34.4339	35.2144	42.7187
0.2588	19.0	2394	0.9968	43.1336	32.2189	33.169	41.8021
0.217	20.0	2520	1.0100	42.957	32.0188	32.6537	41.6299
0.217	21.0	2646	1.0294	43.5366	33.4319	34.3512	42.2255
0.1843	22.0	2772	1.0318	42.612	31.6127	32.6111	41.1739
0.1843	23.0	2898	1.0364	43.3555	33.0608	33.7772	42.0746
0.1621	24.0	3024	1.0472	43.551	33.1728	33.9075	42.3046
0.1621	25.0	3150	1.0489	43.3577	32.7069	33.2761	41.9641
0.1411	26.0	3276	1.0568	43.3813	32.9442	33.6935	42.014
0.1411	27.0	3402	1.0609	43.4543	33.1567	34.1049	42.0669
0.1313	28.0	3528	1.0629	43.5826	33.403	34.5062	42.2977
0.1313	29.0	3654	1.0672	43.4541	33.1488	34.242	42.1413
0.1196	30.0	3780	1.0661	43.385	32.8564	33.7117	42.0926

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.1
• Datasets 3.0.1
• Tokenizers 0.20.0